CN113375275A

CN113375275A - Air conditioner control method and air conditioner

Info

Publication number: CN113375275A
Application number: CN202110719298.1A
Authority: CN
Inventors: 胡敏志; 吕根贵; 谭裕锋
Original assignee: Hisense Guangdong Air Conditioning Co Ltd
Current assignee: Hisense Guangdong Air Conditioning Co Ltd
Priority date: 2021-06-28
Filing date: 2021-06-28
Publication date: 2021-09-10
Anticipated expiration: 2041-06-28
Also published as: CN113375275B

Abstract

The invention discloses an air conditioner control method and an air conditioner, wherein the air conditioner control method comprises the following steps: acquiring the head temperature of a target user; inputting the head temperature into a user individual temperature and coldness decision tree model to determine a temperature and coldness state of the target user; and adjusting the current set temperature according to the temperature and cold feeling state of the target user. The air conditioner control method can adjust the air outlet temperature according to the head temperature of the individual user, realize individual heat comfort control of the user and meet the individual comfort requirements of the user.

Description

Air conditioner control method and air conditioner

Technical Field

The invention relates to the technical field of air conditioners, in particular to an air conditioner control method and an air conditioner.

Background

In the related art, the air conditioner generally adjusts the outlet air temperature through a single temperature index. However, the air conditioner cannot adjust the indoor ambient temperature to the comfortable temperature of the human body well only according to a single temperature index, so that the user feels poor and the requirement of the user on the comfort level cannot be met.

Disclosure of Invention

The present invention is directed to solving at least one of the problems of the prior art. Therefore, an object of the present invention is to provide an air conditioner control method, which can adjust the outlet air temperature according to the head temperature of an individual user, thereby implementing individual thermal comfort control for the user and meeting the individual comfort requirements of the user.

An embodiment of a first aspect of the present invention provides an air conditioner control method, including: acquiring the head temperature of a target user; inputting the head temperature into a user individual temperature and coldness decision tree model to determine a temperature and coldness state of the target user; and adjusting the current set temperature according to the temperature and cold feeling state of the target user.

According to the air conditioner control method provided by the embodiment of the invention, the function of individual temperature and cold feeling of the user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, and the heat and comfort requirement, namely the temperature and cold feeling state of the target user is obtained by inputting the head temperature of the target user into the individual temperature and cold feeling decision tree model of the user, so that the air conditioner can conveniently adjust the current set temperature according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner meets the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the individual use comfort of the user is improved.

An embodiment of a second aspect of the present invention provides an air conditioner control device, including: the temperature acquisition module is used for acquiring the head temperature of a target user; the temperature and cold feeling state determining module is used for inputting the head temperature into a user individual temperature and cold feeling decision tree model so as to determine the temperature and cold feeling state of the target user; and the adjusting module is used for adjusting the current set temperature according to the temperature and cold feeling state of the target user.

According to the air conditioner control device provided by the embodiment of the invention, the function of individual temperature and cold feeling of the user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, the head temperature of the target user is input into the individual temperature and cold feeling decision tree model of the user through the temperature and cold feeling state determination module so as to acquire the thermal comfort requirement, namely the temperature and cold feeling state of the target user, so that the current set temperature can be conveniently adjusted by the adjustment module according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner meets the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the use comfort of the individual user is improved.

A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the air conditioner control method of the above-described embodiments.

An embodiment of a fourth aspect of the present invention provides an air conditioner including the air conditioner control device according to the above embodiment; alternatively, the air conditioner includes: at least one processor; a memory communicatively coupled to the at least one processor; wherein, the memory stores a computer program executable by the at least one processor, and the at least one processor implements the air conditioner control method according to the above embodiment when executing the computer program.

According to the air conditioner provided by the embodiment of the invention, the function of individual temperature and cold feeling of the user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, and the heat and comfort requirement, namely the temperature and cold feeling state of the target user is obtained by inputting the head temperature of the target user into the individual temperature and cold feeling decision tree model of the user, so that the air conditioner can conveniently adjust the current set temperature according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner meets the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the individual use comfort of the user is improved.

An embodiment of a fifth aspect of the present invention provides an air conditioner, including: the system comprises a compressor, an indoor heat exchanger, an outdoor heat exchanger, a four-way valve and a throttling element; the temperature acquisition device is used for acquiring the head temperature of a user; and the controller is connected with the temperature acquisition device and used for adjusting the current set temperature according to the air conditioner control method in the embodiment.

According to the air conditioner provided by the embodiment of the invention, the function of individual temperature and cold feeling of the user can be identified by utilizing the individual temperature and cold feeling decision tree model of the user, the head temperature of the target user is input into the individual temperature and cold feeling decision tree model of the user through the controller, so that the thermal comfort requirement, namely the temperature and cold feeling state of the target user is accurately obtained, the current set temperature can be conveniently adjusted by the air conditioner according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner meets the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the use comfort of the individual users is improved.

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

fig. 1 is a flowchart of an air conditioner control method according to an embodiment of the present invention;

fig. 2 is a flowchart of an air conditioner control method according to another embodiment of the present invention;

FIG. 3 is a schematic diagram of a user individual temperature and coldness decision tree model, according to one embodiment of the present invention;

fig. 4 is a flowchart of an air conditioner control method according to another embodiment of the present invention;

fig. 5 is a structural view of an air conditioner control device according to an embodiment of the present invention;

fig. 6 is a structural view of an air conditioner according to an embodiment of the present invention.

Detailed Description

Embodiments of the present invention will be described in detail below, the embodiments described with reference to the drawings being illustrative, and the embodiments of the present invention will be described in detail below.

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The air conditioner performs a refrigeration cycle of the air conditioner by using a compressor, a condenser, an expansion valve, and an evaporator. The refrigeration cycle includes a series of processes involving compression, condensation, expansion, and evaporation, and supplies refrigerant to the air that has been conditioned and heat-exchanged.

The compressor compresses a refrigerant gas in a high-temperature and high-pressure state and discharges the compressed refrigerant gas. The discharged refrigerant gas flows into the condenser. The condenser condenses the compressed refrigerant into a liquid phase, and heat is released to the surrounding environment through the condensation process.

The expansion valve expands the liquid-phase refrigerant in a high-temperature and high-pressure state condensed in the condenser into a low-pressure liquid-phase refrigerant. The evaporator evaporates the refrigerant expanded in the expansion valve and returns the refrigerant gas in a low-temperature and low-pressure state to the compressor. The evaporator can achieve a cooling effect by heat-exchanging with a material to be cooled using latent heat of evaporation of a refrigerant. The air conditioner can adjust the temperature of the indoor space throughout the cycle.

The outdoor unit of the air conditioner refers to a portion of a refrigeration cycle including a compressor and an outdoor heat exchanger, the indoor unit of the air conditioner includes an indoor heat exchanger, and an expansion valve may be provided in the indoor unit or the outdoor unit.

The indoor heat exchanger and the outdoor heat exchanger serve as a condenser or an evaporator. When the indoor heat exchanger is used as a condenser, the air conditioner is used as a heater in a heating mode, and when the indoor heat exchanger is used as an evaporator, the air conditioner is used as a cooler in a cooling mode.

An air conditioner according to some embodiments of the present application includes an air conditioner indoor unit installed in an indoor space. The indoor unit, i.e., the indoor unit, is connected to an outdoor unit, i.e., the outdoor unit, installed in an outdoor space through a pipe. The outdoor unit of the air conditioner may be provided with a compressor, an outdoor heat exchanger, an outdoor fan, an expander, and the like for a refrigeration cycle, and the indoor unit of the air conditioner may be provided with an indoor heat exchanger and an indoor fan.

In the related art, the air conditioner is usually designed and controlled by a single temperature index, or by using a single temperature index and a single humidity index. However, the air conditioner only adjusts according to a single temperature index and a single humidity index, and does not completely consider factors affecting human thermal sensation, such as air temperature, air relative humidity, wind speed, average radiation temperature, human activity intensity, clothing thermal resistance, etc., so that a user stays in an indoor environment created by the air conditioner for a long time and is very easy to get 'air conditioning sickness', and therefore, the technical problem that the requirements of people on comfort and health can not be effectively met by adjusting the single temperature index and the single humidity index is solved.

In order to solve the above problem, an embodiment of a first aspect of the present invention provides an air conditioner control method, which can adjust an outlet air temperature according to a head temperature of an individual user, so as to implement an individualized thermal comfort control for the user, and meet an individualized comfort requirement of the user.

An air conditioner control method according to an embodiment of the present invention is described below with reference to the accompanying drawings, and as shown in fig. 1, the method includes at least steps S1 through S3.

In step S1, the head temperature of the target user is acquired.

Because the existing control mode of the air conditioner takes the average thermal sensation index established on the basis of common people as reference, for example, a PMV (Predicted Mean volume) model adopted by the air conditioner is an average cold and thermal sensation prediction model based on most users in the same environment, and the influence of individual difference of the users is weakened, the embodiment of the invention judges the own thermal comfort requirement of the users according to the head temperature of the individual users so as to meet the individual thermal comfort requirement of the users, thereby facilitating the air conditioner to execute a corresponding control strategy according to the individual thermal comfort requirement of the users, performing individual thermal comfort control on the users and meeting the individual comfort requirement of the users.

In an embodiment, an infrared device such as an infrared camera may be provided on the air conditioner to collect the head temperature of the target user and transmit the collected data to the controller of the air conditioner.

Step S2, inputting the head temperature into the user individual temperature and coldness decision tree model to determine the temperature and coldness status of the target user.

In the embodiment, aiming at different heat and comfort requirements of individual family users, the embodiment of the invention utilizes an artificial intelligence technology based on big data to self-learn the temperature and cold change rule of the user to establish the individual body temperature and cold decision tree model of the user, and realizes the purpose of accurately identifying the individual heat and comfort requirements of the user, so that after the individual body temperature and cold decision tree model of the user is applied to the air conditioner, the air conditioner can judge the individual heat and comfort requirements of the user according to the individual body temperature and cold decision tree model of the user, and carries out personalized heat and comfort control, thereby meeting the requirements of different individual user on differentiated and personalized comfort control.

The personal body temperature and cold feeling decision tree model of the user is established based on the big data artificial intelligence technology, and the modeling process is as follows.

1) And (6) data acquisition. Compared with a PMV model with physical meanings, the accuracy of the artificial intelligence technology based on big data in the aspect of predicting human body thermal sensation is higher than that of a conventional physical model, and the accuracy of the artificial intelligence technology is greatly dependent on the data volume participating in training, so that in practical application, along with the continuous increase of the data volume, the accuracy of the established model can be improved, and therefore, in order to enable the air conditioner to accurately identify the thermal sensation state of a user, the data acquisition comprises the acquisition of environmental state parameters under various environments and the acquisition of body surface data of different people, wherein the various environments are a plurality of environments in different regions, different seasons, different weather and the like; the environmental state parameters comprise indoor environmental temperature, environmental relative humidity, wind speed, clothing thermal resistance and other state parameters; different people are sampling crowds with different age groups, different sexes, different ethnicities and other physical characteristics; the body surface data of a human body comprises skin temperature, human body heat sensation, human body metabolic rate and the like of a plurality of different human body parts. Therefore, a model training big database is established based on the collected data, so that the temperature and cold feeling change rule of the user can be learned by self through the artificial intelligence technology, and the accuracy of recognizing the individual heat and comfort requirement of the user can be improved when the air conditioner is applied.

2) And (5) training a model. The method comprises the steps of constructing a temperature and cold sensing decision tree prediction model by utilizing skin temperature data of different human body parts, and carrying out model screening, debugging and optimization on the temperature and cold sensing decision tree prediction model by using collected environmental state parameters, human body heat sensing, human body metabolic rate and other parameters under various environments. Under the ideal condition, the temperature and coldness decision tree prediction model established based on the skin temperature can be automatically controlled, the temperature and coldness change rule of the user can be self-learned, the parameter adjustment is not needed to be carried out manually, and the modeling efficiency is improved.

3) And generating a model. Parameters which cannot be directly optimized through an algorithm, namely, hyperparameters exist in the construction process of the decision tree model, the optimal temperature and cold feeling decision tree prediction model which is manually participated in the adjustment and selection training of the hyperparameters is output, and the optimal temperature and cold feeling decision tree prediction model is the needed individual temperature and cold feeling decision tree model of the user.

4) And (6) performing prediction. And testing the optimal temperature and cold feeling decision tree prediction model, predicting to obtain the model accuracy, and judging the generalization degree of the optimal temperature and cold feeling decision tree prediction model.

Therefore, based on the collected parameters such as skin temperature, human body thermal sensation, room temperature, relative humidity, wind speed, metabolic rate, clothing thermal resistance and the like, a model training big database is formed by the above method, and the artificial intelligence technology is utilized to self-learn the temperature and cold sensation change rule of the user so as to finally establish a user individual temperature and cold sensation decision tree model capable of accurately identifying the individual heat and comfort requirements of the user, so that when the user individual temperature and cold sensation decision tree model is applied to the air conditioner, the method is different from a prediction comfort mode applied in the air conditioner and aiming at a plurality of users, the method of the embodiment of the invention can directly identify and predict the temperature and cold sensation of the individual user by utilizing the user individual temperature and cold sensation decision tree model so as to accurately obtain the heat and comfort requirements of the user, namely the temperature and cold sensation state, and further generates a corresponding control strategy by the prediction result of the user, the indoor environment temperature can be conveniently adjusted to the individual comfortable temperature of the user, so that the purpose of the individual optimal comfortable state of the user is achieved, and the individual differentiation and personalized comfortable adjustment requirements of the family user are met.

In addition, different from the method that only a single temperature index is used as the reference for the comfort control of the air conditioner, the embodiment of the invention comprehensively considers the human body physical sign state parameters under different environments when the personal body temperature and cold feeling decision tree model of the user is established, such as various factors influencing the human body heat feeling: the temperature and cold sensing decision tree prediction model is debugged and optimized according to the air temperature, the air relative humidity, the air speed, the average radiation temperature, the human activity intensity, the clothing thermal resistance and the like, so that when the user individual temperature and cold sensing decision tree model is applied to the air conditioner, the air outlet temperature is adjusted through the user individual temperature and cold sensing decision tree model, and the requirements of the user individual on comfort and health can be effectively met.

The temperature sensing state can be understood as the sensing condition of the user on the temperature. The temperature and cold sensing state can be classified into various states according to actual conditions without limitation, and for example, the temperature and cold sensing state can be classified into a cold state, a neutral state and a hot state according to predicted heat sensing conditions. It can be understood that the more the classification of the state of the sensation of warmth and coldness is, the more accurate the result of identifying the individual sensation of warmth and coldness of the user is, and the more comfortable the individual user can be improved.

In the embodiment, the user individual comprises a plurality of skin parts, and the artificial intelligence technology is utilized, the model is continuously debugged and optimized based on big data, and finally the head part with the characteristic of representing the human body temperature cold feeling in the plurality of skin parts and the corresponding temperature decision condition are used for establishing and forming the user individual body temperature cold feeling decision tree model, specifically, the temperature decision conditions at some parts in the head part with the characteristic of representing the human body temperature cold feeling are combined, such as cheek temperature decision condition, nose temperature decision condition, eye temperature decision condition and forehead temperature decision condition, or ear temperature decision condition, cheek temperature decision condition, nose temperature decision condition and eye temperature decision condition, or cheek temperature decision condition, nose temperature decision condition, forehead temperature decision condition, eye temperature decision condition and ear temperature decision condition are respectively used as different layer temperature decision conditions, the user individual temperature and cold feeling decision tree model formed by the method can accurately judge the self heat and comfort requirement of the user, namely the temperature and cold feeling state. Furthermore, when the temperature-sensing device is applied to an air conditioner, the controller can acquire the temperature-sensing state of the target user after the temperature-sensing condition of each layer is judged by inputting the acquired head temperature of the target user into the individual body temperature-sensing decision tree model of the user.

Specifically, a user individual body temperature and cold feeling decision tree model is prestored in a controller of the air conditioner, when a single user exists in an indoor space, the controller of the air conditioner inputs the acquired head temperature into the user individual body temperature and cold feeling decision tree model, and the user individual body temperature and cold feeling decision tree model identifies and predicts the individual body temperature and cold feeling of the user so as to accurately know the heat comfort requirement, namely the body temperature and cold feeling state of the user, so that the air conditioner can generate a corresponding control strategy according to the body temperature and cold feeling state of the user, and the individual comfort requirement of the user can be met.

And step S3, adjusting the current set temperature according to the temperature and cold feeling state of the target user.

Wherein the current set temperature is a temperature stored in a controller of the air conditioner. For example, the current set temperature may be a temperature stored after the controller of the air conditioner performs algorithm processing on the user set temperature and the environmental load parameter; or, when the air conditioner operates a comfort control mode of the TMS (Thermal and comfort Management System), the currently set temperature may be a comfort stage target temperature corresponding to a current operation comfort stage stored by a controller of the air conditioner, wherein the TMS comfort control mode includes an initial comfort stage, a stable comfort stage and a healthy comfort stage that are sequentially set along a time sequence, different comfort stage target temperatures correspond to different comfort stage targets under different comfort stages, and the controller stores the comfort stage target temperature of the current operation comfort stage when the air conditioner operates a certain comfort stage.

In the embodiment, after the temperature and cold feeling state of the target user is determined, the air conditioner can generate a corresponding control strategy according to the temperature and cold feeling state of the user to adjust the current set temperature, so that the indoor environment temperature is adjusted to the individual comfortable temperature of the user, the purpose of achieving the individual optimal comfortable state of the user is achieved, and the individual comfortable requirement of the user is met.

It can be understood that, in order to meet the individual comfort needs of the user, the method of the embodiment of the present invention is suitable for the situation where there is a single user in the indoor space, and the user is the target user, and the individual thermal comfort needs of the user are identified by collecting the head temperature of the user. That is, when a single user exists in the indoor space, the infrared device on the air conditioner may automatically collect the head temperature of the user and operate in the control manner of steps S1-S3 provided above according to the embodiment of the present invention, thereby satisfying the personalized comfort requirement of the user; when a plurality of users exist in the indoor space, the air conditioner automatically operates in a common control mode, such as a TMS comfort control mode, so that the comfort requirement of each user is met. Therefore, the air conditioner can meet the individual comfortable requirements of a single family user, can meet the comfortable requirements of common people, and improves the use comfort of the user.

For example, taking fig. 2 as an example, the overall control method of the air conditioner includes the following steps.

And step S4, the air conditioner operates the TMS comfort control mode.

In step S5, the air conditioner collects the indoor ambient temperature and the indoor ambient relative humidity.

And step S6, the air conditioner operates a user personalized comfort control mode, namely, the individual temperature and cold feeling states of the user are identified by using the individual temperature and cold feeling decision tree model of the user.

Step S7, when a plurality of users exist in the indoor space, calculating a target temperature and a target humidity according to the indoor environment temperature and the indoor environment relative humidity, and controlling the air conditioner to operate according to the target temperature and the target humidity so as to meet the comfort requirement of each user; the temperature and humidity comparison table is stored in the air conditioner and is shown in table 1, namely corresponding default relative humidity is set corresponding to different temperatures, when a single user exists in an indoor space, the current set temperature is adjusted according to the head temperature of the target user, namely the target temperature is calculated, the target humidity corresponding to the target temperature is obtained, and the air conditioner is controlled to operate according to the target temperature and the target humidity, so that the indoor environment meets the personalized comfort requirement of the user.

In step S8, the air conditioner is automatically operated according to the target temperature and the target humidity.

TABLE 1

In some embodiments, the head temperature of the target user is input into a user individual body temperature and cold feeling decision tree model, wherein the user individual body temperature and cold feeling decision tree model is configured with a plurality of temperature decision branches, each temperature decision branch is configured with a plurality of layers of temperature decision conditions, the head temperature is sequentially compared with the plurality of layers of temperature decision conditions in the temperature decision branches in sequence to determine the target temperature decision branch which is satisfied by the head temperature, an output value of the target temperature decision branch corresponding to the user individual body temperature and cold feeling decision tree model is obtained, and a temperature and cold feeling state corresponding to the output value is taken as a temperature and cold feeling state of the target user. In such a way, the individual temperature and cold feeling of the target user is identified and predicted by using the individual temperature and cold feeling decision tree model of the user, so that the temperature and cold feeling state of the target user is accurately obtained, and the air conditioner can conveniently generate a corresponding strategy according to the temperature and cold feeling state to meet the comfortable requirement of the target user.

For convenience of storage and recording of the air conditioner, when a program is preset in the air conditioner, different temperature-sensitive states are respectively represented by different numerical values, for example, when the temperature-sensitive states include a cold state, a neutral state, and a hot state, a numerical value "1" may be used to represent a hot state, a numerical value "0" may be used to represent a neutral state, and a numerical value "-1" may be used to represent a cold state, or other numerical values may be used to represent different temperature-sensitive states, without limitation. In this way, after the target temperature determination branch that the head temperature satisfies is determined, the temperature and cold sensing state of the target user can be known according to the output value of the target temperature determination branch, and if the output value of the target temperature determination branch is 1, it is indicated that the temperature and cold sensing state of the target user is a partial heat.

Specifically, for a user individual body temperature and cold feeling decision tree model, the user individual body temperature and cold feeling decision tree model comprises a plurality of temperature decision branches, each temperature decision branch comprises a plurality of layers of temperature decision conditions, each layer of temperature decision condition represents a possible decision result, in the traversing process from a starting point to an end point of the user individual body temperature and cold feeling decision tree model, a decision is executed once at each layer of temperature decision condition, the output decision result aiming at the difference of each layer of temperature decision condition can lead to different temperature decision branches, the end point of a certain temperature decision branch can be reached finally, the end point of each temperature decision branch corresponds to a temperature and cold feeling state, namely, each temperature decision branch executes independent temperature and cold feeling decision. Based on the method, when the head temperature of the target user is input, the head temperature of the target user is judged by utilizing the plurality of temperature judgment branches of the individual body temperature and cold feeling decision tree model of the user, so that the temperature judgment branch to which the head temperature of the target user belongs is determined, the temperature judgment branch is the target temperature judgment branch, and the temperature and cold feeling state of the target user can be accurately obtained according to the output value of the target temperature judgment branch, so that a subsequent air conditioner can generate a corresponding strategy according to the temperature and cold feeling state to meet the comfortable requirement of the target user.

In some embodiments, the controller of the air conditioner may periodically input the head temperature of the target user into the user individual temperature and cooling sensation decision tree model, count a preset number of output values output by the user individual temperature and cooling sensation decision tree model, and classify the preset number of output values to use a temperature and cooling sensation state corresponding to an output value in a classification containing the largest output value as the temperature and cooling sensation state of the target user. According to the method, the temperature-sensitive state of the target user is judged for multiple times, and the final temperature-sensitive state of the target user is determined according to the prediction result obtained by each judgment, so that the accuracy of the temperature-sensitive state identification of the target user can be improved, and the use comfort of the target user is improved.

That is to say, the air conditioner may collect the head temperature of the target user once at a certain interval, judge and store the head temperature collected each time until the collection frequency of the air conditioner reaches the preset collection frequency, that is, the number of output values reaches the preset number, further count the output values of the corresponding target temperature judgment branches obtained after the judgment of the head temperature collected each time, and take the temperature and cold sensing state corresponding to the output value with the largest number of output values among all the output values as the temperature and cold sensing state of the target user. For example, taking a numerical value "1" to represent a hot bias, a numerical value "0" to represent a neutral state, and a numerical value "-1" to represent a cold bias as an example, the air conditioner collects the head temperature of the target user five times, and the output values obtained after judging the head temperature collected each time are sequentially: 1. 1, 0, 1 and 1, wherein the number of the output values 1 is the largest, and therefore, the bias heat corresponding to the output value 1 is the temperature and cold feeling state of the target user. Therefore, the head temperature is periodically judged to determine the temperature and cold feeling state of the target user, the problem of misjudgment can be avoided, and the accuracy of the air conditioner in identifying the temperature and cold feeling state of the target user is improved.

It should be noted that each time the judgment period of the temperature and cold feeling state of the user is based on the feedback time of the air conditioner.

The following describes inputting the temperature of the target extraction point into the user individual body temperature and coldness decision tree model to determine the state of the target user's body temperature and coldness.

In some embodiments, in the user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization by using an artificial intelligence technology, an ear temperature decision condition, a cheek temperature decision condition, a nose temperature decision condition and an eye temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and coldness decision tree model formed by the above is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes ear temperature T1, cheek temperature T2, nose temperature T3, and eye temperature T4.

First temperature determination branch: t11 is more than or equal to T1, T12 is more than or equal to T2, T13 is more than or equal to T3, and the output values are correspondingly colder; second temperature determination branch: t1 is not less than T11, T2 is not less than T12, T3 is more than T13, the output value corresponds to neutral, wherein T13 is more than T12 is more than T11.

A third temperature determination branch: t1 is not less than T11, T2 is more than T12, T1 is not less than T14, and the output value is neutral; fourth temperature determination branch: t1 is less than or equal to T11, T2 is T12, T1 is T14, the output value is relatively cold, wherein T14 is less than T11.

Fifth temperature determination branch: t1 is more than T11, T1 is less than or equal to T15, T3 is less than or equal to T16, and the output value is neutral; sixth temperature determination branch: t1> T11, T1 ≦ T15, T3> T16, and the output value corresponds to neutral, wherein T15> T16> T13.

Seventh temperature determination branch: t1 is more than T11, T1 is more than T15, T4 is less than or equal to T17, and the output value corresponds to bias heat; eighth temperature determination branch: t1> T11, T1> T15, T4> T17, and the output value corresponds to neutral, wherein T17> T15.

Based on the above eight temperature determination branches of the user individual temperature and coldness decision tree model configuration, the determination process for the input ear temperature T1, cheek temperature T2, nose temperature T3, and eye temperature T4 is as follows.

If the ear temperature T1 is determined to be less than or equal to the first temperature value T11, the cheek temperature T2 is further determined to be less than or equal to the second temperature value T12, and the nose temperature T3 is further determined to be less than or equal to the third temperature value T13, the target temperature determination branch is a first temperature determination branch, the output value of the first temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a partial cold output value, and the state of the body temperature and cold feeling of the target user is partial cold.

Or, it is determined that the ear temperature T1 is less than or equal to the first temperature value T11, it is further determined that the cheek temperature T2 is less than or equal to the second temperature value T12, and it is further determined that the nose temperature T3 is greater than the third temperature value T13, the target temperature determination branch is a second temperature determination branch, the output value of the second temperature determination branch corresponding to the obtained user individual body temperature and cooling sensation decision tree model is a neutral output value, and the state of the target user's body temperature and cooling sensation is neutral.

Or, it is determined that ear temperature T1 is less than or equal to first temperature value T11, cheek temperature T2 is greater than second temperature value T12, and ear temperature T1 is less than or equal to fourth temperature value T14, the target temperature determination branch is a third temperature determination branch, the output value of the third temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, and the temperature and cooling sensation state of the target user is neutral.

Or determining that the ear temperature T1 is less than or equal to the first temperature value T11, further determining that the cheek temperature T2 is greater than the second temperature value T12, and further determining that the ear temperature T1 is greater than the fourth temperature value T14, the target temperature determination branch is a fourth temperature determination branch, and if the output value of the fourth temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a partial cold output value, the state of the body temperature and cold feeling of the target user is partial cold.

Or determining that the ear temperature T1 is greater than the first temperature value T11, further determining that the ear temperature T1 is less than or equal to a fifth temperature value T15, and further determining that the nose temperature T3 is less than or equal to a sixth temperature value T16, the target temperature determination branch is a fifth temperature determination branch, and if the output value of the fifth temperature determination branch corresponding to the user individual temperature and cooling sensation decision tree model is a neutral output value, the temperature and cooling sensation state of the target user is neutral.

Or determining that the ear temperature T1 is greater than the first temperature value T11, further determining that the ear temperature T1 is less than or equal to a fifth temperature value T15, and further determining that the nose temperature T3 is greater than a sixth temperature value T16, the target temperature determination branch is a sixth temperature determination branch, and if the output value of the sixth temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, the temperature and cooling sensation state of the target user is neutral.

Or determining that the ear temperature T1 is greater than the first temperature value T11, further determining that the ear temperature T1 is greater than the fifth temperature value T15, and further determining that the eye temperature T4 is less than or equal to the seventh temperature value T17, the target temperature determination branch is a seventh temperature determination branch, and if the output value of the seventh temperature determination branch corresponding to the obtained user individual temperature and cold feeling decision tree model is the bias heat output value, the temperature and cold feeling state of the target user is bias heat.

Or determining that the ear temperature T1 is greater than the first temperature value T11, further determining that the ear temperature T1 is greater than the fifth temperature value T15, and further determining that the eye temperature T4 is greater than the seventh temperature value T17, the target temperature determination branch is an eighth temperature determination branch, the output value of the eighth temperature determination branch corresponding to the obtained user individual temperature and cold feeling decision tree model is a neutral output value, and the temperature and cold feeling state of the target user is neutral.

Specifically, as shown in fig. 3, the personal temperature and coldness decision tree model of the user, which is built based on big data through continuous debugging and optimization by using the artificial intelligence technology, is as follows, wherein a numerical value "1" represents a bias heat, a numerical value "0" represents a neutral property, and a numerical value "-1" represents a bias cold.

First temperature determination branch: the ear temperature T1 is not less than a first temperature value T11, the cheek temperature T2 is not less than a second temperature value T12, the nose temperature T3 is not less than a third temperature value T13, and the corresponding output value is a partial cold output value-1, so that the temperature and cold feeling state of the target user is partial cold.

Second temperature determination branch: the ear temperature T1 is not less than a first temperature value T11, the cheek temperature T2 is not less than a second temperature value T12, the nose temperature T3 is greater than a third temperature value T13, and the corresponding output values are neutral output values 0, so that the temperature and cold feeling state of the target user is neutral.

A third temperature determination branch: the ear temperature T1 is not less than a first temperature value T11, the cheek temperature T2 is greater than a second temperature value T12, the ear temperature T1 is not less than a fourth temperature value T14, and the corresponding output value is a neutral output value 0, so that the temperature and cold feeling state of the target user is neutral.

Fourth temperature determination branch: the ear temperature T1 is not more than a first temperature value T11, the cheek temperature T2 is more than a second temperature value T12, the ear temperature T1 is more than a fourth temperature value T14, and the corresponding output values are the partial cold output value-1, so that the temperature and cold feeling state of the target user is partial cold.

Fifth temperature determination branch: the ear temperature T1 is greater than the first temperature value T11, the ear temperature T1 is not less than the fifth temperature value T15, the nose temperature T3 is not less than the sixth temperature value T16, and the corresponding output value is a neutral output value 0, so that the temperature and cold feeling state of the target user is neutral.

Sixth temperature determination branch: the ear temperature T1 is greater than the first temperature value T11, the ear temperature T1 is less than or equal to the fifth temperature value T15, the nose temperature T3 is greater than the sixth temperature value T16, and the corresponding output values are neutral output values 0, so that the temperature and cold feeling state of the target user is neutral.

Seventh temperature determination branch: the ear temperature T1 is greater than the first temperature value T11, the ear temperature T1 is greater than the fifth temperature value T15, the eye temperature T4 is less than or equal to the seventh temperature value T17, the corresponding output value is a heat bias output value 1, and the temperature and cold feeling state of the target user is heat bias.

Eighth temperature determination branch: the ear temperature T1 is greater than the first temperature value T11, the ear temperature T1 is greater than the fifth temperature value T15, the eye temperature T4 is greater than the seventh temperature value T17, and the corresponding output values are neutral output values 0, so that the temperature and cold feeling state of the target user is neutral.

Therefore, the head temperature of the target user is judged by utilizing the eight temperature judgment branches configured by the user individual body temperature and coldness decision tree model, the temperature and coldness state of the target user can be accurately obtained, the air conditioner can adjust the current set temperature according to the temperature and coldness state of the user, the air outlet temperature of the air conditioner meets the individual comfortable requirement of the user, the individual differentiation and individual comfortable control requirements of different users are met, and the individual use comfort of the user is improved.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization, a cheek temperature decision condition, an eye temperature decision condition, a nose temperature decision condition and a forehead temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and coldness decision tree model formed by the above steps is configured with seven temperature decision branches, the temperature decision branches are configured with two layers of temperature decision conditions or three layers of temperature decision conditions, and the seven temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes a cheek temperature T2, an eye temperature T4, a nose temperature T3, and a forehead temperature T5.

Ninth temperature determination branch: t2 is not less than T21, T2 is not less than T22, and the output value corresponds to neutral, wherein T21 is more than T22.

Tenth temperature determination branch: t2 is less than or equal to T21, T2 is greater than T22, T4 is less than or equal to T23, and the output value is correspondingly cold; eleventh temperature determination branch: t2 is less than or equal to T21, T2 is greater than T22, T4 is less than or equal to T23, the output value corresponds to neutral, and T23 is greater than T21.

Twelfth temperature determination branch: t2 is more than T21, T3 is less than or equal to T24, T5 is less than or equal to T25, and the output value is neutral; thirteenth temperature determination branch: t2> T21, T3 ≦ T24, T5> T25, and the output value corresponds to neutral, wherein T24> T25> T23.

Fourteenth temperature determination branch: t2 is more than T21, T3 is more than T24, T2 is less than or equal to T26, and the output value is neutral; fifteenth temperature determination branch: t2> T21, T3> T24, T2> T26, and the output value corresponds to neutral, wherein T26> T24.

Based on the above seven temperature determination branches of the user individual temperature and coldness decision tree model configuration, the determination process for the input cheek temperature T2, eye temperature T4, nose temperature T3, and forehead temperature T5 is as follows.

If the cheek temperature T2 is determined to be less than or equal to the eighth temperature value T21, and the cheek temperature T2 is further determined to be less than or equal to the ninth temperature value T22, the target temperature determination branch is a ninth temperature determination branch, the output value of the ninth temperature determination branch corresponding to the acquired user individual temperature and coldness decision tree model is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or, it is determined that the cheek temperature T2 is less than or equal to the eighth temperature value T21, the cheek temperature T2 is greater than the ninth temperature value T22, and the eye temperature T4 is less than or equal to the tenth temperature value T23, the target temperature determination branch is a tenth temperature determination branch, the output value of the tenth temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a partial cooling output value, and the temperature and cooling sensation state of the target user is partial cooling.

Or, it is determined that the cheek temperature T2 is less than or equal to the eighth temperature value T21, the cheek temperature T2 is greater than the ninth temperature value T22, and the eye temperature T4 is greater than the tenth temperature value T23, the target temperature determination branch is an eleventh temperature determination branch, and the output value of the eleventh temperature determination branch corresponding to the obtained user individual body temperature and coldness decision tree model is a neutral output value, so that the state of the coolness of the target user is neutral.

Or, it is determined that the cheek temperature T2 is greater than the eighth temperature value T21, the nose temperature T3 is less than or equal to the eleventh temperature value T24, and the forehead temperature T5 is less than or equal to the twelfth temperature value T25, the target temperature determination branch is a twelfth temperature determination branch, the output value of the twelfth temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, and the temperature and cooling sensation state of the target user is neutral.

Or, it is determined that the cheek temperature T2 is greater than the eighth temperature value T21, the nose temperature T3 is less than or equal to the eleventh temperature value T24, and the forehead temperature T5 is greater than the twelfth temperature value T25, the target temperature determination branch is a thirteenth temperature determination branch, the output value of the thirteenth temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, and the temperature and cooling sensation state of the target user is neutral.

Or, it is determined that the cheek temperature T2 is greater than the eighth temperature value T21, the nose temperature T3 is greater than the eleventh temperature value T24, and the cheek temperature T2 is less than or equal to the thirteenth temperature value T26, the target temperature determination branch is a fourteenth temperature determination branch, an output value of the fourteenth temperature determination branch corresponding to the obtained user individual body temperature and coldness decision tree model is a neutral output value, and the state of the target user's warmth and coldness is neutral.

Or, it is determined that the cheek temperature T2 is greater than the eighth temperature value T21, the nose temperature T3 is greater than the eleventh temperature value T24, and the cheek temperature T2 is greater than the thirteenth temperature value T26, the target temperature determination branch is a fifteenth temperature determination branch, an output value of the fifteenth temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, and the temperature and cooling sensation state of the target user is neutral.

Therefore, the head temperature of the target user is judged by utilizing the seven temperature judgment branches configured by the user individual body temperature and coldness decision tree model, the temperature and coldness state of the target user can be accurately obtained, the air conditioner can conveniently adjust the current set temperature according to the temperature and coldness state of the user, the air outlet temperature of the air conditioner meets the individual comfortable requirement of the user, the individual differentiation and individual comfortable control requirements of different users are met, and the individual use comfort of the user is improved.

In other embodiments, in the user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization by using an artificial intelligence technology, a nose temperature decision condition, an eye temperature decision condition and a cheek temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, the user individual body temperature and coldness decision tree model formed by the above steps is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes a nose temperature T3, an eye temperature T4, and a cheek temperature T2.

Sixteenth temperature determination branch: t31 is more than or equal to T3, T32 is more than or equal to T4, T33 is more than or equal to T3, and the output values are correspondingly colder; seventeenth temperature determination branch: t3 is not less than T31, T4 is not less than T32, T3 is more than T33, the output value is correspondingly cold, wherein T32 is more than T31 is more than T33.

Eighteenth temperature determination branch: t3 is not less than T31, T4 is more than T32, T3 is not less than T34, and the output value is neutral; nineteenth temperature determination branch: t3 is less than or equal to T31, T4 is greater than T32, T3 is greater than T34, the output value is neutral, and T31 is greater than T34 and T33.

Twentieth temperature determination branch: t3 is more than T31, T3 is less than or equal to T35, T2 is less than or equal to T36, and the output value is neutral; twenty-first temperature determination branch: t3> T31, T3 ≦ T35, T2> T36, and the output value corresponds to neutral, wherein T35> T36> T32.

Twenty-second temperature determination branch: t3 is more than T31, T3 is more than T35, T4 is less than or equal to T37, and the output value is neutral; twenty-third temperature determination branch: t3> T31, T3> T35, T4> T37, and the output value corresponds to bias heat, wherein T37> T35.

Based on the above eight temperature determination branches of the user individual temperature and coldness decision tree model configuration, the determination process for the input nose temperature T3, eye temperature T4, and cheek temperature T2 is as follows.

Determining that the nose temperature T3 is less than or equal to a fourteenth temperature value T31, further determining that the eye temperature T4 is less than or equal to a fifteenth temperature value T32, and further determining that the nose temperature T3 is less than or equal to a sixteenth temperature value T33, wherein the target temperature determination branch is a sixteenth temperature determination branch, and obtaining that the output value of the sixteenth temperature determination branch corresponding to the individual temperature and cooling sensation decision tree model of the user is a partial cooling output value, and the temperature and cooling sensation state of the target user is partial cooling, wherein the fourteenth temperature value is less than the fifteenth temperature value, and the sixteenth temperature value is less than the fourteenth temperature value.

Or, it is determined that the nose temperature T3 is less than or equal to the fourteenth temperature value T31, it is further determined that the eye temperature T4 is less than or equal to the fifteenth temperature value T32, and it is further determined that the nose temperature T3 is greater than the sixteenth temperature value T33, then the target temperature determination branch is a seventeenth temperature determination branch, and the output value of the seventeenth temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a partial cold output value, then the state of the target user's temperature and cold feeling is partial cold.

Or, it is determined that the nose temperature T3 is less than or equal to the fourteenth temperature value T31, it is further determined that the eye temperature T4 is greater than the fifteenth temperature value T32, and it is further determined that the nose temperature T3 is less than or equal to the seventeenth temperature value T34, then the target temperature determination branch is an eighteenth temperature determination branch, and the output value of the eighteenth temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a neutral output value, then the state of the target user's temperature and cold feeling is neutral, where the seventeenth temperature value is greater than the sixteenth temperature value and less than the fourteenth temperature value.

Or, it is determined that the nose temperature T3 is less than or equal to the fourteenth temperature value T31, it is further determined that the eye temperature T4 is greater than the fifteenth temperature value T32, and it is further determined that the nose temperature T3 is greater than the seventeenth temperature value T34, the target temperature determination branch is a nineteenth temperature determination branch, the output value of the nineteenth temperature determination branch corresponding to the obtained user individual body temperature and coldness decision tree model is a neutral output value, and the state of the coolness of the target user is neutral.

Or determining that the nose temperature T3 is greater than the fourteenth temperature value T31, further determining that the nose temperature T3 is less than or equal to the eighteenth temperature value T35, and further determining that the cheek temperature T2 is less than or equal to the nineteenth temperature value T36, the target temperature determination branch is a twentieth temperature determination branch, and obtaining that the output value of the twentieth temperature determination branch corresponding to the individual body temperature and cooling sensation decision tree model of the user is a neutral output value, so that the state of the body temperature and cooling sensation of the target user is neutral, where the eighteenth temperature value is greater than the nineteenth temperature value, and the nineteenth temperature value is greater than the fifteenth temperature value.

Or determining that the nose temperature T3 is greater than the fourteenth temperature value T31, further determining that the nose temperature T3 is less than or equal to the eighteenth temperature value T35, and further determining that the cheek temperature T2T3 is greater than the nineteenth temperature value T36, wherein the target temperature determination branch is a twenty-first temperature determination branch, the output value of the twenty-first temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a neutral output value, and the state of the body temperature and cold feeling of the target user is neutral.

Or determining that the nose temperature T3 is greater than the fourteenth temperature value T31, further determining that the nose temperature T3 is greater than the eighteenth temperature value T35, and further determining that the eye temperature T4 is less than or equal to the twentieth temperature value T37, the target temperature determination branch is a twenty-second temperature determination branch, and obtaining that the output value of the twenty-second temperature determination branch corresponding to the user individual body temperature and cold feeling decision tree model is a neutral output value, so that the state of the target user's temperature and cold feeling is neutral, where the twentieth temperature value is greater than the eighteenth temperature value.

Or determining that the nose temperature T3 is greater than the fourteenth temperature value T31, further determining that the nose temperature T3 is greater than the eighteenth temperature value T35, and further determining that the eye temperature T4 is greater than the twentieth temperature value T37, the target temperature determination branch is a twenty-third temperature determination branch, and if the output value of the twenty-third temperature determination branch corresponding to the individual body temperature and cold feeling decision tree model of the user is the bias heat output value, the state of the body temperature and cold feeling of the target user is the bias heat.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization, a cheek temperature decision condition, a forehead temperature decision condition, a nose temperature decision condition and an eye temperature decision condition are used as temperature decision conditions in each temperature decision branch correspondingly, and the user individual body temperature and coldness decision tree model formed by the above is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes a cheek temperature T2, a forehead temperature T5, a nose temperature T3, and an eye temperature T4.

Twenty-fourth temperature determination branch: t41 is more than or equal to T2, T42 is more than or equal to T5, T43 is more than or equal to T2, and the output value is neutral; twenty-fifth temperature determination branch: t2 is not less than T41, T5 is not less than T42, T2 is more than T43, the output value is correspondingly cold, wherein T42 is more than T41 is more than T43.

Twenty-sixth temperature determination branch: t2 is less than or equal to T41, T5 is greater than T42, T3 is less than or equal to T44, and the output value is correspondingly cold; twenty-seventh temperature determination branch: t2 is less than or equal to T41, T5 is greater than T42, T3 is greater than T44, the output value corresponds to neutral, and T43 is greater than T44.

Twenty-eighth temperature determination branch: t2 is more than T41, T3 is less than or equal to T45, T2 is less than or equal to T46, and the output value is neutral; twenty-ninth temperature determination branch: t2> T41, T3 ≦ T45, T2> T46, and the output value corresponds to neutral, wherein T45> T46> T42.

Thirtieth temperature determination branch: t2 is more than T41, T3 is more than T45, T4 is less than or equal to T47, and the output value is neutral; thirty-first temperature determination branch: t2> T41, T3> T45, T4> T47, and the output value corresponds to neutral, wherein T47> T45.

Based on the above eight temperature determination branches configured by the user individual temperature and coldness decision tree model, the determination process for the input cheek temperature T2, forehead temperature T5, nose temperature T3, and eye temperature T4 is as follows.

And determining that the cheek temperature T2 is less than or equal to a twenty-first temperature value T41, the forehead temperature T5 is less than or equal to a twenty-second temperature value T42, and the cheek temperature T2 is less than or equal to a twenty-third temperature value T43, wherein the target temperature determination branch is a twenty-fourth temperature determination branch, the output value of the twenty-fourth temperature determination branch corresponding to the acquired user individual temperature and coldness decision tree model is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or determining that the cheek temperature T2 is less than or equal to a twenty-first temperature value T41, further determining that the forehead temperature T5 is less than or equal to a twenty-second temperature value T42, and further determining that the cheek temperature T2 is greater than a twenty-third temperature value T43, the target temperature determination branch is a twenty-fifth temperature determination branch, and if the output value of the twenty-fifth temperature determination branch corresponding to the user individual temperature and coldness decision tree model is obtained as a cold bias output value, the temperature and coldness state of the target user is a cold bias.

Or determining that the cheek temperature T2 is less than or equal to a twenty-first temperature value T41, further determining that the forehead temperature T5 is greater than a twenty-second temperature value T42, and further determining that the nose temperature T3 is less than or equal to a twenty-fourth temperature value T44, the target temperature determination branch is a twenty-sixth temperature determination branch, and if the output value of the twenty-sixth temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a partial cold output value, the temperature and coldness state of the target user is partial cold.

Or determining that the cheek temperature T2 is less than or equal to the twenty-first temperature value T41, further determining that the forehead temperature T5 is greater than the twenty-second temperature value T42, and further determining that the nose temperature T3 is greater than the twenty-fourth temperature value T44, the target temperature determination branch is a twenty-seventh temperature determination branch, and the output value of the twenty-seventh temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a neutral output value, so that the state of the body temperature and cold feeling of the target user is neutral.

Or determining that the cheek temperature T2 is greater than the twenty-first temperature value T41, further determining that the nose temperature T3 is less than or equal to the twenty-fifth temperature value T45, and further determining that the cheek temperature T2 is less than or equal to the twenty-sixth temperature value T46, the target temperature determination branch is a twenty-eighth temperature determination branch, and the output value of the twenty-eighth temperature determination branch corresponding to the obtained user individual body temperature and coldness decision tree model is a neutral output value, so that the state of the target user's warmness and coldness is neutral.

Or determining that the cheek temperature T2 is greater than the twenty-first temperature value T41, further determining that the nose temperature T3 is less than or equal to the twenty-fifth temperature value T45, and further determining that the cheek temperature T2 is greater than the twenty-sixth temperature value T46, the target temperature determination branch is a twenty-ninth temperature determination branch, and the output value of the twenty-ninth temperature determination branch corresponding to the obtained user individual body temperature and coldness decision tree model is a neutral output value, so that the state of the warmness and coldness of the target user is neutral.

Or determining that the cheek temperature T2 is greater than the twenty-first temperature value T41, further determining that the nose temperature T3 is greater than the twenty-fifth temperature value T45, and further determining that the eye temperature T4 is less than or equal to the twenty-seventh temperature value T47, wherein the target temperature determination branch is a thirtieth temperature determination branch, the output value of the thirtieth temperature determination branch corresponding to the obtained individual body temperature and cold feeling decision tree model is a neutral output value, and the state of the body temperature and cold feeling of the target user is neutral.

Or determining that the cheek temperature T2 is greater than the twenty-first temperature value T41, further determining that the nose temperature T3 is greater than the twenty-fifth temperature value T45, and further determining that the eye temperature T4 is greater than the twenty-seventh temperature value T47, the target temperature determination branch is a thirty-first temperature determination branch, and if the output value of the thirty-first temperature determination branch corresponding to the obtained individual body temperature and coldness decision tree model of the user is a neutral output value, the state of the coolness of the target user is neutral.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization, an eye temperature decision condition, a cheek temperature decision condition, an ear temperature decision condition and a nose temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and coldness decision tree model formed by the above is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes an eye temperature T4, a cheek temperature T2, an ear temperature T1, and a nose temperature T3.

Thirty-second temperature determination branch: t51 is more than or equal to T4, T52 is more than or equal to T2, T53 is more than or equal to T1, and the output values are correspondingly colder; thirty-third temperature determination branch: t4 is not less than T51, T2 is not less than T52, T1 is more than T53, the output value corresponds to neutral, wherein T51 is more than T52 is more than T53.

Thirty-fourth temperature determination branch: t4 is less than or equal to T51, T2 is greater than T52, T3 is less than or equal to T54, and the output value is correspondingly cold; thirty-fifth temperature determination branch: t4 is less than or equal to T51, T2 is greater than T52, T3 is greater than T54, the output value is neutral, and T51 is greater than T54 and T52.

Thirty-sixth temperature determination branch: t4 is more than T51, T4 is less than or equal to T55, T1 is less than or equal to T56, and the output value is neutral; thirty-seventh temperature determination branch: t4> T51, T4 ≦ T55, T1> T56, and the output value corresponds to neutral, wherein T56> T55> T51.

Thirty-eighth temperature determination branch: t4 is more than T51, T4 is more than T55, T2 is less than or equal to T57, and the output value is neutral; thirty-ninth temperature determination branch: t4> T51, T4> T55, T2> T57, and the output value corresponds to neutral, wherein T55> T57> T51.

The determination process for the input eye temperature T4, cheek temperature T2, ear temperature T1, and nose temperature T3 based on the eight temperature determination branches of the user's individual psychrometric decision tree model configuration is as follows.

And determining that the eye temperature T4 is less than or equal to a twenty-eighth temperature value T51, further determining that the cheek temperature T2 is less than or equal to a twenty-ninth temperature value T52, and further determining that the ear temperature T1 is less than or equal to a thirty-third temperature value T53, wherein the target temperature determination branch is a thirty-second temperature determination branch, the output value of the thirty-second temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a partial cold output value, and the temperature and cold feeling state of the target user is partial cold.

Or determining that the eye temperature T4 is less than or equal to a twenty-eighth temperature value T51, further determining that the cheek temperature T2 is less than or equal to a twenty-ninth temperature value T52, and further determining that the ear temperature T1 is greater than a thirty-third temperature value T53, the target temperature determination branch is a thirty-third temperature determination branch, and the output value of the thirty-third temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a neutral output value, so that the state of the body temperature and cold feeling of the target user is neutral.

Or determining that the eye temperature T4 is less than or equal to a twenty-eighth temperature value T51, further determining that the cheek temperature T2 is greater than a twenty-ninth temperature value T52, and further determining that the nose temperature T3 is less than or equal to a thirty-first temperature value T54, the target temperature determination branch is a thirty-fourth temperature determination branch, and the output value of the thirty-fourth temperature determination branch corresponding to the obtained user individual body temperature and cold feeling decision tree model is a partial cold output value, so that the temperature and cold feeling state of the target user is partial cold.

Or determining that the eye temperature T4 is less than or equal to a twenty-eighth temperature value T51, further determining that the cheek temperature T2 is greater than a twenty-ninth temperature value T52, and further determining that the nose temperature T3 is greater than a thirty-eleventh temperature value T54, the target temperature determination branch is a thirty-fifth temperature determination branch, and the output value of the thirty-fifth temperature determination branch corresponding to the obtained user body temperature and cold feeling decision tree model is a neutral output value, so that the state of the target user body temperature and cold feeling is neutral.

Or determining that the eye temperature T4 is greater than a twenty-eighth temperature value T51, further determining that the eye temperature T4 is less than or equal to a thirty-second temperature value T55, and further determining that the ear temperature T1 is less than or equal to a thirty-third temperature value T56, wherein the target temperature determination branch is a thirty-sixth temperature determination branch, the output value of the thirty-sixth temperature determination branch corresponding to the obtained user body temperature and cold feeling decision tree model is a neutral output value, and the temperature and cold feeling state of the target user is neutral.

Or determining that the eye temperature T4 is greater than the twenty-eighth temperature value T51, further determining that the eye temperature T4 is less than or equal to the thirty-second temperature value T55, and further determining that the ear temperature T1 is greater than the thirty-third temperature value T56, the target temperature determination branch is a thirty-seventh temperature determination branch, the output value of the thirty-seventh temperature determination branch corresponding to the obtained user body temperature and cold feeling decision tree model is a neutral output value, and the state of the body temperature and cold feeling of the target user is neutral.

Or determining that the eye temperature T4 is greater than the twenty-eighth temperature value T51, further determining that the eye temperature T4 is greater than the thirty-second temperature value T55, and further determining that the cheek temperature T2 is less than or equal to the thirty-fourth temperature value T57, the target temperature determination branch is a thirty-eighth temperature determination branch, the output value of the thirty-eighth temperature determination branch corresponding to the obtained user body temperature and coldness decision tree model is a neutral output value, and the state of the coolness of the target user is neutral.

Or determining that the eye temperature T4 is greater than the twenty-eighth temperature value T51, further determining that the eye temperature T4 is greater than the thirty-second temperature value T55, and further determining that the cheek temperature T2 is greater than the thirty-fourth temperature value T57, the target temperature determination branch is a thirty-ninth temperature determination branch, the output value of the thirty-ninth temperature determination branch corresponding to the obtained user body temperature and coldness decision tree model is a neutral output value, and the state of the coolness of the target user is neutral.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and cold feeling decision tree model established based on big data through continuous debugging and optimization, a cheek temperature decision condition, a forehead temperature decision condition, an ear temperature decision condition and a nose temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and cold feeling decision tree model formed by the above steps is configured with seven temperature decision branches, the temperature decision branches are configured with two-layer temperature decision conditions or three-layer temperature decision conditions, and the seven temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes cheek temperature T2, forehead temperature T5, ear temperature T4 and nose temperature T3.

Fortieth temperature determination branch: t61 is more than or equal to T2, T62 is more than or equal to T5, T63 is more than or equal to T4, and the output values are correspondingly colder; forty-first temperature determination branch: t2 is not less than T61, T5 is not less than T62, T4 is more than T63, the output value corresponds to neutral, wherein T62 is more than T61 is more than T63.

Forty-second temperature determination branch: t2 is less than or equal to T61, T5 is greater than T62, and the output value corresponds to neutral.

Forty-third temperature determination branch: t2 is more than T61, T3 is less than or equal to T64, T3 is less than or equal to T65, and the output value is neutral; forty-fourth temperature determination branch: t2 is more than T61, T3 is less than or equal to T64, T3 is more than T65, the output value is neutral, and T64 is more than T62 is more than T65 is more than T61.

Forty-fifth temperature determination branch: t2 is more than T61, T3 is more than T64, T4 is less than or equal to T66, and the output value is neutral; forty-sixth temperature determination branch: t2> T61, T3> T64, T4> T66, and the output value corresponds to neutral, wherein T66> T64.

Based on the above seven temperature determination branches of the user individual temperature and coldness decision tree model configuration, the determination process for the input cheek temperature T2, forehead temperature T5, ear temperature T4, and nose temperature T3 is as follows.

And determining that the cheek temperature T2 is less than or equal to a thirty-fifth temperature value T61, further determining that the forehead temperature T5 is less than or equal to a thirty-sixth temperature value T62, and further determining that the ear temperature T4 is less than or equal to a thirty-seventh temperature value T63, wherein the target temperature determination branch is a fortieth temperature determination branch, the output value of the fortieth temperature determination branch corresponding to the obtained individual body temperature and cold feeling decision tree model is a partial cold output value, and the temperature and cold feeling state of the target user is partial cold.

Or determining that the cheek temperature T2 is less than or equal to a thirty-fifth temperature value T61, further determining that the forehead temperature T5 is less than or equal to a thirty-sixth temperature value T62, and further determining that the ear temperature T4 is greater than a thirty-seventh temperature value T63, the target temperature determination branch is a forty-first temperature determination branch, and the output value of the forty-first temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a neutral output value, so that the temperature and coldness state of the target user is neutral.

Or, it is determined that the cheek temperature T2 is less than or equal to the thirty-fifth temperature value T61, and it is further determined that the forehead temperature T5 is greater than the thirty-sixth temperature value T62, the target temperature determination branch is a forty-second temperature determination branch, an output value of the forty-second temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or determining that the cheek temperature T2 is greater than a thirty-fifth temperature value T61, further determining that the nose temperature T3 is less than or equal to a thirty-eighth temperature value T64, and further determining that the nose temperature T3 is less than or equal to a thirty-ninth temperature value T65, the target temperature determination branch is a forty-third temperature determination branch, and the output value of the forty-third temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a neutral output value, so that the temperature and coldness state of the target user is neutral.

Or determining that the cheek temperature T2 is greater than a thirty-fifth temperature value T61, further determining that the nose temperature T3 is less than or equal to a thirty-eighth temperature value T64, and further determining that the nose temperature T3 is greater than a thirty-ninth temperature value T65, the target temperature determination branch is a forty-fourth temperature determination branch, and the output value of the forty-fourth temperature determination branch corresponding to the obtained user body temperature and coldness decision tree model is a neutral output value, so that the state of the target user's warmth and coldness is neutral.

Or determining that the cheek temperature T2 is greater than a thirty-fifth temperature value T61, further determining that the nose temperature T3 is greater than a thirty-eighth temperature value T64, and further determining that the ear temperature T4 is less than or equal to a forty-fifth temperature value T66, the target temperature determination branch is a forty-fifth temperature determination branch, and if the output value of the forty-fifth temperature determination branch corresponding to the user individual body temperature and coldness decision tree model is a neutral output value, the target user's state of warmness and coldness is determined.

Or determining that the cheek temperature T2 is greater than a thirty-fifth temperature value T61, further determining that the nose temperature T3 is greater than a thirty-eighth temperature value T64, and further determining that the ear temperature T4 is greater than a forty-fifth temperature value T66, the target temperature determination branch is a forty-sixth temperature determination branch, and if the output value of the forty-sixth temperature determination branch corresponding to the obtained individual body temperature and coldness decision tree model of the user is a neutral output value, the state of the target user's coolness is neutral.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization, a cheek temperature decision condition, a nose temperature decision condition, a forehead temperature decision condition, an eye temperature decision condition and an ear temperature decision condition are used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and coldness decision tree model formed by the above steps is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes cheek temperature T2, nose temperature T3, forehead temperature T5, eye temperature T4, and ear temperature T1.

Forty-seventh temperature determination branch: t71 is more than or equal to T2, T72 is more than or equal to T3, T73 is more than or equal to T5, and the output values are correspondingly colder; forty-eighth temperature determination branch: t2 is not less than T71, T3 is not less than T72, T5 is more than T73, the output value is correspondingly cold, wherein T73 is more than T71 is more than T72.

Forty-ninth temperature determination branch: t2 is not less than T71, T3 is more than T72, T4 is not less than T74, and the output value is neutral; fifth temperature determination branch: t2 is less than or equal to T71, T3 is greater than T72, T4 is greater than T74, the output value corresponds to neutral, and T74 is greater than T73.

Fifty-first temperature determination branch: t2 is more than T71, T2 is less than or equal to T75, T1 is less than or equal to T76, and the output value is neutral; fifty-second temperature determination branch: t2 is more than T71, T2 is less than or equal to T75, T1 is more than T76, the output value is neutral, wherein T75 is more than T74, T71 is more than T76 is more than T72.

Fifty-third temperature determination branch: t2 is more than T71, T2 is more than T75, T5 is less than or equal to T77, and the output value is neutral; fifty-fourth temperature determination branch: t2> T71, T2> T75, T5> T77, and the output value corresponds to neutral, wherein T77> T75.

Based on the above eight temperature determination branches configured by the user individual temperature and coldness decision tree model, the determination process for the input cheek temperature T2, nose temperature T3, forehead temperature T5, eye temperature T4, and ear temperature T1 is as follows.

And determining that the cheek temperature T2 is less than or equal to a forty-first temperature value T71, the nose temperature T3 is less than or equal to a forty-second temperature value T72, and the forehead temperature T5 is less than or equal to a forty-third temperature value T73, wherein the target temperature determination branch is a forty-seventh temperature determination branch, the output value of the forty-seventh temperature determination branch corresponding to the obtained individual body temperature and cold feeling decision tree model is a cold bias output value, and the state of the body temperature and cold feeling of the target user is cold bias.

Or, it is determined that the cheek temperature T2 is less than or equal to the forty-first temperature value T71, the nose temperature T3 is less than or equal to the forty-second temperature value T72, and the forehead temperature T5 is greater than the forty-third temperature value T73, the target temperature determination branch is a forty-eighth temperature determination branch, and the output value of the forty-eighth temperature determination branch corresponding to the obtained individual body temperature and coldness decision tree model is a partial cold output value, so that the state of the body temperature and coldness of the target user is partial cold.

Or, it is determined that the cheek temperature T2 is less than or equal to the forty-first temperature value T71, the nose temperature T3 is greater than the forty-second temperature value T72, and the eye temperature T4 is less than or equal to the forty-fourth temperature value T74, the target temperature determination branch is a forty-ninth temperature determination branch, the output value of the forty-ninth temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or, it is determined that the cheek temperature T2 is less than or equal to the forty-first temperature value T71, the nose temperature T3 is greater than the forty-second temperature value T72, and the eye temperature T4 is greater than the forty-fourth temperature value T74, the target temperature determination branch is a fifty-th temperature determination branch, the output value of the fifty-th temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model is a neutral output value, and the state of the warmth and coldness of the target user is neutral.

Or, it is determined that cheek temperature T2 is greater than forty-first temperature value T71, cheek temperature T2 is less than or equal to forty-fifth temperature value T75, and ear temperature T1 is less than or equal to forty-sixth temperature value T76, the target temperature determination branch is a fifty-first temperature determination branch, the output value of the fifty-first temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model is a neutral output value, and the state of the target user's warmth and coldness is neutral.

Or determining that the cheek temperature T2 is greater than a forty-first temperature value T71, further determining that the cheek temperature T2 is less than or equal to a forty-fifth temperature value T75, and further determining that the ear temperature T1 is greater than a forty-sixth temperature value T76, if the target temperature determination branch is a fifty-second temperature determination branch, obtaining that the output value of the fifty-second temperature determination branch corresponding to the individual body temperature and coldness decision tree model of the user is a neutral output value, and if the state of the body temperature and coldness of the target user is neutral;

or, it is determined that cheek temperature T2 is greater than forty-first temperature value T71, cheek temperature T2 is greater than forty-fifth temperature value T75, and forehead temperature T5 is less than or equal to forty-seventh temperature value T77, the target temperature determination branch is a fifty-third temperature determination branch, and the target is obtained if the output value of the fifty-third temperature determination branch corresponding to the user individual temperature and coldness decision tree model is a neutral output value.

Or, it is determined that cheek temperature T2 is greater than forty-first temperature value T71, cheek temperature T2 is greater than forty-fifth temperature value T75, and forehead temperature T5 is greater than forty-seventh temperature value T77, the target temperature determination branch is a fifty-fourth temperature determination branch, the output value of the fifty-fourth temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model is a neutral output value, and the state of the body temperature and coldness of the target user is neutral.

In other embodiments, by using an artificial intelligence technology, in a user individual body temperature and coldness decision tree model established based on big data through continuous debugging and optimization, an eye temperature decision condition, a cheek temperature decision condition, a nose temperature decision condition, a forehead temperature decision condition and an ear temperature decision condition are correspondingly used as temperature decision conditions in each temperature decision branch, and the user individual body temperature and coldness decision tree model formed by the above steps is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows. Wherein the acquired head temperature of the target user includes an eye temperature T4, a cheek temperature T2, a nose temperature T3, a forehead temperature T5, and an ear temperature T1.

Fifty-fifth temperature determination branch: t81 is more than or equal to T4, T82 is more than or equal to T2, T83 is more than or equal to T3, and the output values are correspondingly colder; fifty-sixth temperature determination branch: t4 is not less than T81, T2 is not less than T82, T3 is more than T83, the output value corresponds to neutral, wherein T81 is more than T82 is more than T83.

Fifty-seventh temperature determination branch: t4 is not less than T81, T2 is more than T82, T5 is not less than T84, and the output value is neutral; fifty-eighth temperature determination branch: t4 is less than or equal to T81, T2 is greater than T82, T5 is greater than T84, the output value corresponds to neutral, and T84 is greater than T81.

Fifty-ninth temperature determination branch: t4 is more than T81, T5 is less than or equal to T85, T5 is less than or equal to T86, and the output value is neutral; sixty-th temperature determination branch: t4> T81, T5 ≦ T85, T5> T86, and the output value corresponds to neutral, wherein T85> T86> T84.

Sixty-first temperature determination branch: t4 is more than T81, T5 is more than T85, T1 is less than or equal to T87, and the output value is neutral; sixty-second temperature determination branch: t4> T81, T5> T85, T1> T87, and the output value corresponds to bias heat, wherein T87> T85.

Based on the above eight temperature determination branches configured by the user individual temperature and coldness decision tree model, the determination process for the input eye temperature T4, cheek temperature T2, nose temperature T3, forehead temperature T5, and ear temperature T1 is as follows.

Wherein, it is determined that the eye temperature T4 is less than or equal to the forty-eighth temperature value T81, it is further determined that the cheek temperature T2 is less than or equal to the forty-ninth temperature value T82, and it is still further determined that the nose temperature T3 is less than or equal to the fifty-fifth temperature value T83, the target temperature determination branch is a fifty-fifth temperature determination branch, the output value of the acquired user individual body temperature and coldness decision tree model corresponding to the fifty-fifth temperature determination branch is a partial cold output value, and the state of the body temperature and coldness of the target user is a partial cold.

Or, it is determined that the eye temperature T4 is less than or equal to the forty-eighth temperature value T81, it is further determined that the cheek temperature T2 is less than or equal to the forty-ninth temperature value T82, and it is still further determined that the nose temperature T3 is greater than the fifty-fifth temperature value T83, the target temperature determination branch is a fifty-sixth temperature determination branch, the output value of the fifty-sixth temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model of the user is a neutral output value, and the state of the warmth and coldness of the target user is neutral.

Or, it is determined that the eye temperature T4 is less than or equal to the forty-eighth temperature value T81, it is further determined that the cheek temperature T2 is greater than the forty-ninth temperature value T82, and it is still further determined that the forehead temperature T5 is less than or equal to the fifty-first temperature value T84, the target temperature determination branch is a fifty-seventh temperature determination branch, the output value of the fifty-seventh temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model is a neutral output value, and the state of the warmth and coldness of the target user is neutral.

Or, it is determined that the eye temperature T4 is less than or equal to the forty-eighth temperature value T81, it is further determined that the cheek temperature T2 is greater than the forty-ninth temperature value T82, and it is further determined that the forehead temperature T5 is greater than the fifty-first temperature value T84, the target temperature determination branch is a fifty-eighth temperature determination branch, the output value of the fifty-eighth temperature determination branch corresponding to the acquired individual body temperature and coldness decision tree model is a neutral output value, and the state of the warmth and coldness of the target user is neutral.

Or, it is determined that the eye temperature T4 is greater than the forty-eighth temperature value T81, it is further determined that the forehead temperature T5 is less than or equal to the fifty-second temperature value T85, and it is still further determined that the forehead temperature T5 is less than or equal to the fifty-third temperature value T86, the target temperature determination branch is a fifty-ninth temperature determination branch, the output value of the acquired user individual temperature and coldness decision tree model corresponding to the fifty-ninth temperature determination branch is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or, it is determined that the eye temperature T4 is greater than the forty-eighth temperature value T81, it is further determined that the forehead temperature T5 is less than or equal to the fifty-second temperature value T85, and it is further determined that the forehead temperature T5 is greater than the fifty-third temperature value T86, the target temperature determination branch is a sixty temperature determination branch, an output value of the sixty temperature determination branch corresponding to the obtained user individual temperature and coldness decision tree model is a neutral output value, and the temperature and coldness state of the target user is neutral.

Or, it is determined that the eye temperature T4 is greater than the forty-eighth temperature value T81, it is further determined that the forehead temperature T5 is greater than the fifty-second temperature value T85, and it is further determined that the ear temperature T1 is less than or equal to the fifty-fourth temperature value T87, the target temperature determination branch is a sixty-first temperature determination branch, the output value of the sixty-first temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is a neutral output value, and the temperature and cooling sensation state of the target user is neutral.

Or, it is determined that the eye temperature T4 is greater than the forty-eighth temperature value T81, the forehead temperature T5 is greater than the fifty-second temperature value T85, and the ear temperature T1 is greater than the fifty-fourth temperature value T87, the target temperature determination branch is a sixty-second temperature determination branch, the output value of the sixty-second temperature determination branch corresponding to the obtained user individual temperature and cooling sensation decision tree model is the bias heat output value, and the temperature and cooling sensation state of the target user is bias heat.

It should be noted that the first temperature value to the fifty-fourth temperature value mentioned in the user individual body temperature and cold feeling decision tree model are obtained by continuously debugging and optimizing an artificial intelligence technology based on big data, so that the user individual body temperature and cold feeling decision tree model can judge the state of the body temperature and cold feeling of the target user through the temperature values, accurately obtain the thermal comfort requirement of the target user, facilitate the air conditioner to perform personalized thermal comfort control, and meet the personalized comfort regulation requirement of the target user.

In some embodiments, if it is determined that the temperature and cold feeling state of the target user is a partial cold, the current set temperature is increased, that is, when the controller of the air conditioner predicts that the individual temperature and cold feeling of the user is a partial cold through the individual temperature and cold feeling decision tree model of the user, a temperature increase signal is sent to increase the preset temperature on the basis of the stored current set temperature, for example, the preset temperature is 1 ℃, the current set temperature is 20 ℃, and the increased target temperature is 21 ℃; or, if the temperature and cold feeling state of the target user is determined to be neutral, the current set temperature is maintained, that is, when the controller of the air conditioner predicts that the individual temperature and cold feeling of the user is neutral through the individual temperature and cold feeling decision tree model of the user, a temperature maintaining signal is sent to keep the current set temperature unchanged, for example, the preset temperature is 1 ℃, the current set temperature is 20 ℃, and the target temperature is 20 ℃ of the current set temperature in response to the temperature maintaining signal; or, if it is determined that the temperature and cold feeling state of the target user is a bias heat, the current set temperature is decreased, that is, when the controller of the air conditioner predicts that the individual temperature and cold feeling of the user is a bias heat through the individual temperature and cold feeling decision tree model of the user, a cooling signal is sent to decrease the preset temperature on the basis of the stored current set temperature, for example, the preset temperature is 1 ℃, the current set temperature is 20 ℃, and the decreased target temperature is 19 ℃. Therefore, the current set temperature is adjusted in the above mode, so that the air conditioner operates according to the adjusted target temperature, the purpose of performing personalized thermal comfort control on the user is achieved, and the personalized comfort adjustment requirement of the target user is met.

In some embodiments, the air conditioner is in a heating mode, and if the temperature and cold feeling state of the target user is determined to be partial cold continuously for a preset number of times, the rotating speed of an indoor fan of the air conditioner is increased; or the air conditioner is in a heating mode, and if the temperature and cold feeling state of the target user is determined to be bias heat continuously for preset times, the rotating speed of an indoor fan of the air conditioner is reduced; or the air conditioner is in a refrigeration mode, and if the temperature and cold feeling state of the target user is determined to be partial cold by continuous preset times, the rotating speed of an indoor fan of the air conditioner is reduced; and the air conditioner is in a refrigeration mode, and the rotating speed of an indoor fan of the air conditioner is increased if the temperature and cold feeling state of the target user is determined to be a bias heat continuously for preset times. That is, when the user thermal sensation states predicted by the air conditioner for the continuous preset times are all consistent, it is indicated that the individual thermal sensation of the user is strong, and therefore, the personalized thermal comfort control is performed on the user by adjusting the rotating speed of the indoor fan, and the personalized comfort regulation requirement of the target user is met.

It can be understood that, if the temperature and cold feeling state of the target user is determined to be neutral by the continuous preset times, the current air conditioner indoor fan rotating speed is maintained.

The air conditioner control method according to the embodiment of the present invention is described below with reference to fig. 3 and 4, and the detailed steps are as follows.

In step S9, the air conditioner is automatically operated.

And step S10, predicting the temperature and the cold of the individual user by using the individual temperature and cold decision tree model of the user.

In step S11, if it is determined that the user feels neutral, the current set temperature Tset is kept unchanged.

Step S12, if the temperature and cold feeling state of the user is determined to be cold, the current set temperature needs to be increased; if the temperature and cold feeling state of the user is determined to be a partial heat, the current set temperature needs to be reduced.

And step S13, changing the current set temperature stored in the controller once according to the temperature and cold feeling state of the user. If the temperature and cold feeling state of the user is determined to be cold, controlling the current set temperature to be +1 ℃; and if the temperature and cold feeling state of the user is determined to be a partial heat state, controlling the current set temperature to be-1 ℃.

And step S14, judging whether the Tset +3 < the target temperature < Tset-3 is met. If not, the target temperature is not the temperature obtained by the air conditioner through automatic control according to the individual temperature and coldness decision tree model of the user, but the temperature changed by the user through the remote controller in a self-defined way, and in this case, the step S15 is executed; if yes, go to step S16.

In step S15, the target temperature is the maximum value Tset ± 3.

In step S16, the air conditioner calculates a target temperature according to the temperature-sensitive state of the user, i.e., the temperature after the current set temperature is changed in step S13.

In step S17, the air conditioner obtains the default relative humidity RHset according to the target temperature through a temperature and humidity comparison table, such as shown in table 1.

And step S18, operating the cooling mode according to the target temperature and the default relative humidity corresponding to the target temperature.

Step S19, compressor frequency control.

In step S20, the cooling mode is entered for the first time.

And step S21, judging whether the set temperature difference E is more than 3 ℃. The set temperature difference E is an absolute value of a difference between the indoor ambient temperature and the target temperature. If yes, go to step S22; if not, step S23 is executed.

And step S22, calling the existing forced cooling mode to operate.

Step S23, operating in normal mode.

And step S24, controlling the rotating speed of the fan.

And step S25, judging whether the set temperature difference E is more than 2 ℃. If yes, go to step S26; if not, step S28 is executed.

Step S26, run at 1250rpm of ultra-high wind. It should be noted that after the first stroke in this mode, if E > 3 ℃ is detected and lasts for 5min, then the ultrahigh wind is operated.

And step S27, judging whether the set temperature difference E is less than or equal to 2 ℃. If yes, go to step S28; if not, step S26 is executed.

Step S28, run at stroke 1000 rpm.

And step S29, judging whether the continuous four periods-2 is more than or equal to and delta R is less than 2. The indoor instantaneous sampling relative humidity is collected once every preset sampling period such as 5min, and the delta R is the difference value between the indoor instantaneous sampling relative humidity Rhi of the current sampling period and the indoor instantaneous sampling relative humidity RH (i-1) of the last sampling period, namely the delta R is Rhi-RH (i-1). If yes, go to step S30; if not, step S28 is executed.

And step S30, judging whether the-6 is more than or equal to the Delta RH and less than 6. And the delta RH is the difference value between the indoor instantaneous sampling relative humidity Rhi and the default relative humidity RHSet in the current sampling period. If yes, go to step S29; if not, step S31 is executed.

In step S31, it is determined whether Δ RH > 6 is satisfied. If yes, go to step S32; if not, step S33 is executed.

And step S32, shifting down to the wind shield with low wind speed.

In step S33, it is determined whether Δ RH < 6 is satisfied. If yes, go to step S34.

And step S34, shifting up to a wind shield with high wind speed.

Therefore, through the steps, the invention establishes the user individual body temperature and cold feeling decision tree model by utilizing the artificial intelligence technology based on big data aiming at different heat and cold feeling requirements of individual family users, self-learns the change rule of the user body temperature and cold feeling, and accurately identifies the individual body heat and cold feeling requirements of the user, thereby being convenient for the air conditioner to carry out personalized heat and cold comfort control according to the head temperature of a target user when being applied to the air conditioner, meeting the individual differentiation and personalized comfort control requirements of different users, simultaneously making up the defect that the PMV prediction comfort model based on common crowds weakens the individual differentiation, ensuring that the air conditioner not only meets the comfort requirements of common crowds, but also can realize the personalized comfort requirements of single family users.

A second embodiment of the present invention provides an air conditioner control device, as shown in fig. 5, an air conditioner control device 10 includes a temperature acquisition module 1, a temperature and cold feeling state determination module 2, and an adjustment module 3.

The temperature acquisition module 1 is used for acquiring the head temperature of a target user; the temperature and cold feeling state determination module 2 is used for inputting the head temperature into the individual temperature and cold feeling decision tree model of the user so as to determine the temperature and cold feeling state of the target user; the adjusting module 3 is used for adjusting the current set temperature according to the temperature and cold feeling state of the target user.

It should be noted that the specific implementation manner of the air conditioner control device 10 according to the embodiment of the present invention is similar to the specific implementation manner of the air conditioner control method according to any of the above embodiments of the present invention, and please refer to the description of the method part specifically, and details are not described here again in order to reduce redundancy.

According to the air conditioner control device 10 provided by the embodiment of the invention, the function of individual temperature and cold feeling of a user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, the head temperature of the target user is input into the individual temperature and cold feeling decision tree model of the user through the temperature and cold feeling state determination module 2, so that the heat comfort requirement, namely the temperature and cold feeling state of the target user is obtained, the current set temperature can be conveniently adjusted by the adjusting module 3 according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner is enabled to meet the individual comfort requirement of the user, the individual differentiation and individual comfort control requirements of different users are realized, and the use comfort of the individual users is improved.

An embodiment of a third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the air conditioner control method provided by the above-described embodiment.

An embodiment of a fourth aspect of the present invention provides an air conditioner, and the air conditioner according to the embodiment of the present invention is described below.

In an embodiment of the present invention, the air conditioner may include the air conditioner control device 10 provided in the above-described embodiment. Namely, the air conditioner controls the air outlet temperature through the air conditioner control device 10, so that personalized thermal comfort control is realized, and personalized comfort regulation requirements of target users are met.

In this embodiment, a specific implementation manner of the air conditioner is similar to that of the air conditioner control device 10 according to any of the above embodiments of the present invention, and please refer to the description of the air conditioner control device 10 for details, which will not be described herein again in order to reduce redundancy.

In another embodiment of the present invention, an air conditioner may include at least one processor and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor, and the at least one processor implements the air conditioner control method provided by the above embodiment when executing the computer program.

In this embodiment, a specific implementation manner of the air conditioner is similar to that of the air conditioner control method according to any of the above embodiments of the present invention, and please refer to the description of the air conditioner control method portion specifically, and details are not repeated here in order to reduce redundancy.

According to the air conditioner provided by the embodiment of the invention, the function of individual temperature and cold feeling of the user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, and the heat and comfort requirement, namely the temperature and cold feeling state of the target user is obtained by inputting the head temperature of the target user into the individual temperature and cold feeling decision tree model of the user, so that the air conditioner can conveniently adjust the current set temperature according to the temperature and cold feeling state of the user, the air outlet temperature of the air conditioner meets the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the individual use comfort of the user is improved.

A fourth embodiment of the present invention provides an air conditioner, as shown in fig. 6, the air conditioner 20 includes a compressor 4, an indoor heat exchanger 5, an indoor fan 6, an outdoor heat exchanger 7, an outdoor fan 8, a throttling element 9, a temperature collecting device 11, and a controller 12.

The temperature acquisition device 11 is used for acquiring the head temperature of a user; the controller 12 is connected to the temperature collecting device 11, and is used for adjusting the current set temperature according to the air conditioner control method provided in the above embodiment.

In some embodiments, the temperature acquisition device 11 may be an infrared device such as an infrared camera. The temperature collecting device 11 may be disposed at a suitable position of the air conditioner, such as on a control panel of the indoor unit, so as to collect the head temperature of the user in real time.

In this embodiment, a specific implementation manner of the controller is similar to that of the air conditioner control method according to any of the above embodiments of the present invention, and please refer to the description of the air conditioner control method portion specifically, and details are not repeated here in order to reduce redundancy.

According to the air conditioner 20 of the embodiment of the invention, the function of individual temperature and cold feeling of the user can be accurately identified by utilizing the individual temperature and cold feeling decision tree model of the user, the head temperature of the target user is input into the individual temperature and cold feeling decision tree model of the user through the controller 12, so that the heat comfort requirement, namely the temperature and cold feeling state of the target user is obtained, the current set temperature can be conveniently adjusted by the air conditioner 20 according to the temperature and cold feeling state of the user, the outlet air temperature of the air conditioner is enabled to meet the individual comfort requirement of the user, and therefore, the individual differentiation and individual comfort control requirements of different users are realized, and the individual use comfort of the user is improved.

Other configurations and operations of the air conditioner according to the embodiment of the present invention are known to those skilled in the art and will not be described in detail herein.

The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.

In the description of this specification, any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of custom logic functions or processes, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present invention.

The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example.

While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. An air conditioner control method, comprising:

acquiring the head temperature of a target user;

inputting the head temperature into a user individual temperature and coldness decision tree model to determine a temperature and coldness state of the target user;

and adjusting the current set temperature according to the temperature and cold feeling state of the target user.

2. The air conditioner control method according to claim 1, wherein inputting the head temperature into a user individual psychrometric decision tree model to determine the target user's psychrometric state comprises:

inputting the head temperature into the user individual body temperature and coldness decision tree model, wherein the user individual body temperature and coldness decision tree model is configured with a plurality of temperature decision branches, and each temperature decision branch is configured with a plurality of layers of temperature decision conditions;

sequentially comparing the head temperature with a plurality of layers of temperature decision conditions in the temperature decision branches in sequence to determine a target temperature decision branch which is satisfied by the head temperature;

acquiring an output value of the target temperature judgment branch corresponding to the user individual body temperature and cold feeling decision tree model;

and taking the temperature sensing state corresponding to the output value as the temperature sensing state of the target user.

3. The air conditioner controlling method according to claim 2,

the inputting the head temperature of the target user into the user individual body temperature and coldness decision tree model comprises: periodically inputting the head temperature into the user individual temperature and coldness decision tree model;

the taking the temperature-sensitive state corresponding to the output value as the temperature-sensitive state of the target user includes:

counting the output values of the preset number output by the user individual temperature and cold feeling decision tree model;

classifying the output values of the preset number;

and taking the temperature and cold feeling state corresponding to the output value in the classification containing the most output values as the temperature and cold feeling state of the target user.

4. The air conditioner controlling method according to claim 1,

the head temperature includes ear temperature T1, cheek temperature T2, nose temperature T3, and eye temperature T4;

the user individual body temperature and cold feeling decision tree model is configured with eight temperature decision branches, each temperature decision branch is configured with three layers of temperature decision conditions, and the eight temperature decision branches are configured as follows:

first temperature determination branch: t1 is not less than T11, T2 is not less than T12, T3 is not less than T13, the output value is relatively cold, and the second temperature determination branch comprises: t1 is not less than T11, T2 is not less than T12, T3 is more than T13, the output value is neutral, wherein T13 is more than T12 is more than T11;

a third temperature determination branch: t1 is less than or equal to T11, T2 is greater than T12, T1 is less than or equal to T14, the output value corresponds to neutral, and the fourth temperature determination branch comprises: t1 is less than or equal to T11, T2 is T12, T1 is T14, the output value is relatively cold, wherein T14 is less than T11;

fifth temperature determination branch: t1> T11, T1 is less than or equal to T15, T3 is less than or equal to T16, the output value corresponds to neutral, and the sixth temperature determination branch comprises: t1 is more than T11, T1 is less than or equal to T15, T3 is more than T16, the output value is neutral, wherein T15 is more than T16 is more than T13;

seventh temperature determination branch: t1> T11, T1> T15, T4 is less than or equal to T17, the output value corresponds to the bias heat, and the eighth temperature determination branch comprises the following steps: t1> T11, T1> T15, T4> T17, and the output value corresponds to neutral, wherein T17> T15.

5. The air conditioner controlling method according to claim 1,

the head temperature includes cheek temperature T2, eye temperature T4, nose temperature T3, and forehead temperature T5;

the user individual body temperature and cold feeling decision tree model is configured with seven temperature decision branches, the temperature decision branches are configured with two layers of temperature decision conditions or three layers of temperature decision conditions, and the seven temperature decision branches are configured as follows:

ninth temperature determination branch: t2 is not less than T21, T2 is not less than T22, the output value corresponds to neutral, wherein T21 is more than T22;

tenth temperature determination branch: t2 is less than or equal to T21, T2 is greater than T22, T4 is less than or equal to T23, the output value is relatively cold, and an eleventh temperature determination branch comprises the following steps: t2 is not less than T21, T2 is T22, T4 is not less than T23, the output value is neutral, wherein T23 is T21;

twelfth temperature determination branch: t2> T21, T3 is less than or equal to T24, T5 is less than or equal to T25, the output value corresponds to neutral, and a thirteenth temperature determination branch comprises: t2 is more than T21, T3 is less than or equal to T24, T5 is more than T25, the output value is neutral, wherein T24 is more than T25 is more than T23;

fourteenth temperature determination branch: t2> T21, T3> T24, T2 is less than or equal to T26, the output value corresponds to neutral, and the fifteenth temperature determination branch comprises the following components: t2> T21, T3> T24, T2> T26, and the output value corresponds to neutral, wherein T26> T24.

6. The air conditioner controlling method according to claim 1,

the head temperature includes a nose temperature T3, an eye temperature T4, and a cheek temperature T2;

sixteenth temperature determination branch: t3 is less than or equal to T31, T4 is less than or equal to T32, T3 is less than or equal to T33, the output value is relatively cold, and a seventeenth temperature judgment branch comprises: t3 is not less than T31, T4 is not less than T32, T3 is more than T33, the output value is correspondingly cold, wherein T32 is more than T31 is more than T33;

eighteenth temperature determination branch: t3 is less than or equal to T31, T4 is greater than T32, T3 is less than or equal to T34, the output value corresponds to neutral, and a nineteenth temperature judgment branch comprises the following components: t3 is less than or equal to T31, T4 is greater than T32, T3 is greater than T34, the output value is neutral, and T31 is greater than T34 is greater than T33;

twentieth temperature determination branch: t3 is more than T31, T3 is less than or equal to T35, T2 is less than or equal to T36, the output value corresponds to neutral, and the twenty-first temperature judgment branch comprises the following steps: t3 is more than T31, T3 is less than or equal to T35, T2 is more than T36, the output value is neutral, wherein T35 is more than T36 is more than T32;

twenty-second temperature determination branch: t3> T31, T3> T35, T4 is less than or equal to T37, the output value corresponds to neutral, and the twenty-third temperature determination branch comprises the following steps: t3> T31, T3> T35, T4> T37, and the output value corresponds to bias heat, wherein T37> T35.

7. The air conditioner controlling method according to claim 1,

the head temperature includes cheek temperature T2, forehead temperature T5, nose temperature T3, and eye temperature T4;

twenty-fourth temperature determination branch: t2 is not less than T41, T5 is not less than T42, T2 is not less than T43, the output value corresponds to neutral, and the twenty-fifth temperature judgment branch comprises: t2 is not less than T41, T5 is not less than T42, T2 is more than T43, the output value is correspondingly cold, wherein T42 is more than T41 is more than T43;

twenty-sixth temperature determination branch: t2 is less than or equal to T41, T5 is greater than T42, T3 is less than or equal to T44, the output value is relatively cold, and a twenty-seventh temperature judgment branch comprises the following steps: t2 is less than or equal to T41, T5 is greater than T42, T3 is greater than T44, the output value is neutral, and T43 is greater than T44;

twenty-eighth temperature determination branch: t2 is more than T41, T3 is less than or equal to T45, T2 is less than or equal to T46, the output value corresponds to neutral, and a twenty-ninth temperature judgment branch comprises the following steps: t2 is more than T41, T3 is less than or equal to T45, T2 is more than T46, the output value is neutral, wherein T45 is more than T46 is more than T42;

thirtieth temperature determination branch: t2> T41, T3> T45, T4 is less than or equal to T47, the output value corresponds to neutral, and a thirty-one temperature determination branch comprises the following steps: t2> T41, T3> T45, T4> T47, and the output value corresponds to neutral, wherein T47> T45.

8. The air conditioner controlling method according to claim 1,

the head temperature includes eye temperature T4, cheek temperature T2, ear temperature T1, and nose temperature T3;

thirty-second temperature determination branch: t4 is less than or equal to T51, T2 is less than or equal to T52, T1 is less than or equal to T53, the output value is relatively cold, and the thirty-third temperature judgment branch comprises the following steps: t4 is not less than T51, T2 is not less than T52, T1 is more than T53, the output value is neutral, wherein T51 is more than T52 is more than T53;

thirty-fourth temperature determination branch: t4 is less than or equal to T51, T2 is greater than T52, T3 is less than or equal to T54, the output value is relatively cold, and the thirty-fifth temperature determination branch comprises the following steps: t4 is less than or equal to T51, T2 is greater than T52, T3 is greater than T54, the output value is neutral, and T51 is greater than T54 is greater than T52;

thirty-sixth temperature determination branch: t4> T51, T4 is less than or equal to T55, T1 is less than or equal to T56, the output value corresponds to neutral, and the thirty-seventh temperature judgment branch comprises: t4 is more than T51, T4 is less than or equal to T55, T1 is more than T56, the output value is neutral, wherein T56 is more than T55 is more than T51;

thirty-eighth temperature determination branch: t4> T51, T4> T55, T2 is less than or equal to T57, the output value corresponds to neutral, and a thirty-ninth temperature judgment branch comprises the following steps: t4> T51, T4> T55, T2> T57, and the output value corresponds to neutral, wherein T55> T57> T51.

9. The air conditioner controlling method according to claim 1,

the head temperature includes cheek temperature T2, forehead temperature T5, ear temperature T4, and nose temperature T3;

fortieth temperature determination branch: t2 is not less than T61, T5 is not less than T62, T4 is not less than T63, the output value is relatively cold, and the forty-first temperature determination branch: t2 is not less than T61, T5 is not less than T62, T4 is more than T63, the output value is neutral, wherein T62 is more than T61 is more than T63;

forty-second temperature determination branch: t2 is not more than T61, T5 is more than T62, and the output value corresponds to neutral;

forty-third temperature determination branch: t2> T61, T3 ≦ T64, T3 ≦ T65, the output value corresponding to neutral, the forty-fourth temperature determination branch: t2 is more than T61, T3 is less than or equal to T64, T3 is more than T65, the output value is neutral, wherein T64 is more than T62 is more than T65 is more than T61;

forty-fifth temperature determination branch: t2> T61, T3> T64, T4 is less than or equal to T66, the output value corresponds to neutral, and the forty-sixth temperature determination branch: t2> T61, T3> T64, T4> T66, and the output value corresponds to neutral, wherein T66> T64.

10. The air conditioner controlling method according to claim 1,

the head temperature includes cheek temperature T2, nose temperature T3, forehead temperature T5, eye temperature T4, and ear temperature T1;

forty-seventh temperature determination branch: t2 is less than or equal to T71, T3 is less than or equal to T72, T5 is less than or equal to T73, the output value is relatively cold, and the forty-eighth temperature determination branch comprises: t2 is not less than T71, T3 is not less than T72, T5 is more than T73, the output value is correspondingly cold, wherein T73 is more than T71 is more than T72;

forty-ninth temperature determination branch: t2 ≦ T71, T3> T72, T4 ≦ T74, the output value corresponding to neutral, the fifty-th temperature determination branch: t2 is less than or equal to T71, T3 is greater than T72, T4 is greater than T74, the output value is neutral, and T74 is greater than T73;

fifty-first temperature determination branch: t2> T71, T2 ≦ T75, T1 ≦ T76, the output value corresponding to neutral, the fifty-second temperature determination branch: t2 is more than T71, T2 is less than or equal to T75, T1 is more than T76, the output value is neutral, wherein T75 is more than T74, T71 is more than T76 is more than T72;

fifty-third temperature determination branch: t2> T71, T2> T75, T5 ≦ T77, the output value corresponding to neutral, the fifty-fourth temperature determination branch: t2> T71, T2> T75, T5> T77, and the output value corresponds to neutral, wherein T77> T75.

11. The air conditioner controlling method according to claim 1,

the head temperature includes eye temperature T4, cheek temperature T2, nose temperature T3, forehead temperature T5, and ear temperature T1;

fifty-fifth temperature determination branch: t4 is not less than T81, T2 is not less than T82, T3 is not less than T83, the output value is relatively cold, and a fifty-sixth temperature determination branch: t4 is not less than T81, T2 is not less than T82, T3 is more than T83, the output value is neutral, wherein T81 is more than T82 is more than T83;

fifty-seventh temperature determination branch: t4 ≦ T81, T2> T82, T5 ≦ T84, the output value corresponding to neutral, the fifty-eighth temperature determination branch: t4 is less than or equal to T81, T2 is greater than T82, T5 is greater than T84, the output value is neutral, and T84 is greater than T81;

fifty-ninth temperature determination branch: t4> T81, T5 is less than or equal to T85, T5 is less than or equal to T86, the output value corresponds to neutral, and the sixty-th temperature judgment branch comprises: t4 is more than T81, T5 is less than or equal to T85, T5 is more than T86, the output value is neutral, wherein T85 is more than T86 is more than T84;

sixty-first temperature determination branch: t4> T81, T5> T85, T1 is less than or equal to T87, the output value corresponds to neutral, and the sixty-second temperature determination branch comprises: t4> T81, T5> T85, T1> T87, and the output value corresponds to bias heat, wherein T87> T85.

12. The air conditioner controlling method according to any one of claims 4 to 11, wherein adjusting the current set temperature according to the state of the target user's feeling of warmth comprises:

if the temperature and cold feeling state of the target user is determined to be cold, the current set temperature is increased;

if the temperature and cold feeling state of the target user is determined to be neutral, maintaining the current set temperature;

and if the temperature and cold feeling state of the target user is determined to be a partial heat, reducing the current set temperature.

13. The air conditioner control method according to claim 12, further comprising at least one of:

the air conditioner is in a heating mode, and if the temperature and cold feeling state of the target user is determined to be partial cold by continuous preset times, the rotating speed of an indoor fan of the air conditioner is increased;

the air conditioner is in a heating mode, if the temperature and cold feeling state of the target user is determined to be a bias heat continuously for the preset times, the rotating speed of an indoor fan of the air conditioner is reduced;

the air conditioner is in a refrigeration mode, if the temperature and cold feeling state of the target user is determined to be partial cold continuously for the preset times, the rotating speed of an indoor fan of the air conditioner is reduced;

and the air conditioner is in a refrigeration mode, and if the temperature and cold feeling state of the target user is determined to be the bias heat continuously for the preset times, the rotating speed of an indoor fan of the air conditioner is increased.

14. An air conditioner is characterized in that the air conditioner comprises a shell,

the air conditioner includes:

at least one processor;

a memory communicatively coupled to the at least one processor;

wherein the memory has stored therein a computer program executable by the at least one processor, the at least one processor implementing the air conditioner control method of any one of claims 1-13 when executing the computer program.

15. An air conditioner, comprising:

the system comprises a compressor, an indoor heat exchanger, an indoor fan, an outdoor heat exchanger, an outdoor fan and a throttling element;

the temperature acquisition device is used for acquiring the head temperature of a user;

a controller connected to the temperature collecting device for adjusting the current set temperature according to the air conditioner control method of any one of claims 1 to 13.