CN109357352A - Air conditioner intelligent temperature control system and method based on Decision Tree Algorithm - Google Patents
Air conditioner intelligent temperature control system and method based on Decision Tree Algorithm Download PDFInfo
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- CN109357352A CN109357352A CN201811308534.5A CN201811308534A CN109357352A CN 109357352 A CN109357352 A CN 109357352A CN 201811308534 A CN201811308534 A CN 201811308534A CN 109357352 A CN109357352 A CN 109357352A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The invention discloses a kind of air conditioner intelligent temperature control system based on Decision Tree Algorithm, including information acquisition system and control processing system, information acquisition system includes at least ambient temperature data, humidity data, shell temperature data, air quality data, and/or air velocity data for acquiring environmental data, environmental data；It controls and is equipped with categorised decision tree-model in processing system, control processing system is connected with information acquisition system, control processing system carries out classification processing for being input in categorised decision tree-model to the data that information acquisition system acquires, and controls air-conditioning according to the classification results of categorised decision tree-model and execute corresponding operation.System of the invention can promote the intelligence of air-conditioning, realize that air-conditioning more efficiently, explicitly carries out automatically controlling.
Description
Technical field
The present invention relates to smart machine control technology fields, in particular to the air conditioner intelligent temperature based on Decision Tree Algorithm
Control system and method.
Background technique
With popularizing for smart machine, household electrical appliance realize intelligence substantially, and more convenient and quicker is people's
Service for life.But existing air-conditioning tends not to be fitted after manually doing exercises in the case where surrounding enviroment change
The regulation of degree has caused air conditioner disease and unnecessary energy waste under the conditions of so that current environment is in optimum.So
It is proposed that this relies on the automatic temperature-controlled method of categorised decision tree to enjoy people to greatest extent in the case where energy saving
The environment of the most comfortable, and improve the user experience of equipment.
Categorised decision tree, decision tree (Decision Tree) are also known as decision tree, are a kind of tree knots for applying to classification
Structure.Each internal node (internal node) therein represents the primary test to some attribute, and each edge represents a survey
Test result, leaf node (leaf) represents the distribution (class distribution) of some class (class) or class, uppermost
Node is root node.Decision tree is divided into classification tree and two kinds of regression tree, and classification tree does decision tree to discrete variable, and regression tree is to even
Continuous variable does decision tree.Decision Tree algorithms have a benefit, that is, it can produce the rule that people can directly understand, this is shellfish
The no characteristic of Ye Si, neural network scheduling algorithm；The accuracy rate of decision tree is also relatively high, and be not required to it is to be understood that background knowledge just
It can classify, be a very effective algorithm.Decision Tree algorithms have many mutation, including ID3, C4.5, C5.0, CART
Deng, but its basis is all similar.
Currently, not occurring also temporarily for categorised decision tree being applied in intelligent air condition, so that air-conditioning has automatic adjustment temperature
Degree is to promote the scheme of user's use feeling.
Summary of the invention
It is insufficient in above-mentioned background technique the purpose of the present invention is overcoming, a kind of air-conditioning based on Decision Tree Algorithm is provided
Intelligent temperature control system and method use the data analysing method of categorised decision tree, more on the basis of existing automatic adjustment
Increase effect, explicitly carry out automatically controlling, to improve recognition accuracy to a certain extent, subtracts while improving user experience
Few discomfort caused by blowing air-conditioning because excessive.
In order to reach above-mentioned technical effect, the present invention takes following technical scheme:
Air conditioner intelligent temperature control system based on Decision Tree Algorithm, including information acquisition system and control processing system,
The information acquisition system includes at least ambient temperature data, humidity data, body for acquiring environmental data, the environmental data
Table temperature data, air quality data, and/or air velocity data；Categorised decision tree mould is equipped in the control processing system
Type, control processing system are connected with information acquisition system, and the data that control processing system is used to acquire information acquisition system are defeated
Enter to carrying out classification processing in categorised decision tree-model, and controls air-conditioning according to the classification results of categorised decision tree-model and execute pair
The operation answered.
Further, the information acquisition system includes at least thermometer, hygrometer, infrared temperature instrument, air quality point
Analysis apparatus and/or air sense of movement answer device.
Meanwhile the invention also discloses a kind of air conditioner intelligent temperature control method based on Decision Tree Algorithm, including it is above-mentioned
The air conditioner intelligent temperature control system based on Decision Tree Algorithm, and specifically includes the following steps:
A. the preset comfortable environment number of human body sensory under normal circumstances in the categorised decision tree-model of control processing system
According to threshold range as categorised decision tree-model to the regulation threshold range of environmental data；The environmental data includes at least ring
Border temperature data, humidity data, shell temperature data, air quality data, and/or air velocity data；
B. environmental data is acquired by information acquisition system and is transferred to control processing system as environmental data to be judged；
C. it is treated in control processing system by categorised decision tree-model and judges that environmental data carries out judging processing and life
At corresponding regulating strategy；
D. control processing system controls air-conditioning according to regulating strategy and executes corresponding operation.
Wherein, the generation step of the categorised decision tree-model in the control processing system is as follows:
S101. using the environmental data under big data acquisition human comfort's environment, the environmental data includes at least environment
Temperature data, humidity data, shell temperature data, air quality data, and/or air velocity data；
S102. the environmental data acquired in step S101 is counted, while people is carried out to the environmental data counted on
Work point class, and the range threshold by manually defining environmental data of all categories according to big data information, and training set is generated respectively
And test data set；
S103. using the training classifier of training set obtained in the step S102, and with test data set to training institute
The classifier obtained is tested, and categorised decision tree-model is obtained.
It further include that minority is obeyed according to majority when specifically, being counted in the step S102 to the environmental data of acquisition
Rule to carry out environmental data cleaning treatment.And preferably, further including step S104: the ring being arranged in conjunction with user's habituation
Border data optimize the range threshold of each classification data in categorised decision tree-model, obtain final categorised decision tree mould
Type.
Further, ambient temperature data regulation threshold range is that environment temperature is not more than T2, is not less than in the step A
T1, it is that air humidity is not less than P1, is not more than P2 that humidity data, which regulates and controls threshold range, and shell temperature data regulation threshold range is
Shell temperature not less than ST1, be not more than ST2, air quality data regulate and control threshold range be air quality index no more than AQI1,
It is that air velocity is not less than V1, is not more than V2 that air velocity data, which regulate and control threshold range,.
Further, in the step C when judging that the ambient temperature data in environmental data is greater than T2, categorised decision
The regulating strategy control air-conditioning of tree-model output carries out cooling processing, and environment temperature is at least reduced to T2, when ring to be judged
When ambient temperature data in the data of border is less than T1, the regulating strategy control air-conditioning of categorised decision tree-model output is carried out at heating
Reason, and environment temperature is at least increased to T1；
When judging that the air humidity data in environmental data are less than P1, the regulating strategy of categorised decision tree-model output
It controls air-conditioning and carries out humidification process, and air humidity is at least increased to P1, when wait judge the air humidity number in environmental data
When according to being greater than P2, the regulating strategy control air-conditioning of categorised decision tree-model output carries out dehumidification treatments, and at least by air humidity
It is reduced to P2；
When judging that the shell temperature data in environmental data are greater than ST2, the regulation plan of categorised decision tree-model output
Slightly control air-conditioning carries out cooling processing, and shell temperature data are at least reduced to ST2, when wait judge the body surface in environmental data
When temperature data is less than ST1, the regulating strategy control air-conditioning of categorised decision tree-model output carries out heating treatment, and at least by body
Table temperature data is increased to ST1；
When judging that the air quality index in environmental data is greater than AQI1, the regulation plan of categorised decision tree-model output
Slightly control air-conditioning carries out air cleaning, and air quality index is at least reduced to AQI1；
When judging that the air velocity data in environmental data are less than V1, the regulating strategy of categorised decision tree-model output
Control air-conditioning breezes up, and air velocity is at least increased to V1, when wait judge that the air velocity data in environmental data are big
When V2, the regulating strategy control air-conditioning of categorised decision tree-model output reduces wind-force, and air velocity is at least reduced to V2.
Further, the regulation threshold range of the environmental data can will be used by user's sets itself or control processing system
The environmental data that family is repeatedly set is as standard environment data and is set in the corresponding environment number of substitution in categorised decision tree-model
According to regulation threshold range.
Further, the control processing system as standard environment data and sets the environmental data that user repeatedly sets
When substituting the regulation threshold range of corresponding environmental data in categorised decision tree-model specifically includes the following steps:
S1. i.e. acquisition user is multiple when the number that user continuously sets a certain environmental data to a certain fixed value is more than a times
The fixed value of the environmental data of sets itself；
S2. the standard value that the fixed value of the environmental data is placed in categorised decision tree-model and as the environmental data is replaced
For the regulation threshold range of corresponding environmental data.
Further, the step B specifically:
B1. information acquisition system acquires the environmental data in a detection cycle and is transferred to control processing system；It is described
One detection cycle is b seconds, and information acquisition system acquired an environmental data every c seconds, wherein b=c*n, n are not less than
1；
B2. control processing system carries out mean value calculation to all kinds of environmental datas in the detection cycle received, and
The average value of all kinds of environmental datas obtained in one cycle is transferred to categorised decision tree-model as environment number to be judged
According to.
Compared with prior art, the present invention have it is below the utility model has the advantages that
Using the air conditioner intelligent temperature control system and method for the invention based on Decision Tree Algorithm, the intelligence of air-conditioning can be promoted
Energyization realizes that air-conditioning more efficiently, explicitly carries out automatically controlling, to improve the usage experience of user, is conducive to promote production
The user satisfaction of product increases the competitiveness of product in market.
Detailed description of the invention
Fig. 1 is the bulk flow of the air conditioner intelligent temperature control method in one embodiment of the present of invention based on Decision Tree Algorithm
Journey schematic diagram.
Fig. 2 is the generation of categorised decision tree-model and the air-conditioning based on Decision Tree Algorithm in one embodiment of the present of invention
The application flow schematic diagram of intelligent temperature control system.
Fig. 3 is the schematic diagram of categorised decision tree-model in one embodiment of the present of invention.
Specific embodiment
Below with reference to the embodiment of the present invention, the invention will be further elaborated.
Embodiment:
Embodiment one:
Air conditioner intelligent temperature control system based on Decision Tree Algorithm, including information acquisition system and control processing system,
Information acquisition system includes at least ambient temperature data, humidity data, shell temperature number for acquiring environmental data, environmental data
According to, air quality data, air velocity data；Control processing system in be equipped with categorised decision tree-model, control processing system with
Information acquisition system is connected, and control processing system is for being input to categorised decision tree-model to the data that information acquisition system acquires
Interior carry out classification processing, and control air-conditioning according to the classification results of categorised decision tree-model and execute corresponding operation.
Specifically, information acquisition system includes at least thermometer, hygrometer, infrared temperature instrument, air matter in the present embodiment
Amount analytical equipment, air sense of movement answer device.
In use, can first preset human body under normal circumstances be suitable for comfortable in the categorised decision tree-model of control processing system
The environmental data range of environment, specifically include the range of environment temperature in the comfortable situation of human body sensory, the range of air humidity,
Range, highest air quality index, the range of air velocity of shell temperature.Above-mentioned data can be obtained by big data technology.
Simultaneously as using categorised decision tree-model in the application, and the categorised decision tree-model has self-aid learning
Function, in actual use, control processing system can be by user's sets itself or a certain environment that repeatedly set of acquisition user
Standard value of the value of data as the environmental data, to substitute preset specific environmental data range when former factory.
If the range of environment temperature preset in the categorised decision tree-model of control processing system when leaving the factory is 18 DEG C
~26 DEG C, but in actual use, user every time adjusts temperature to 22 DEG C, then controlling processing system can be by categorised decision
The range of environment temperature in tree-model is changed to 22 DEG C by 18 DEG C~26 DEG C, in order in actual use, according to different
User carries out personal settings, to better meet the use demand of user.
In use, information acquisition system pass through respectively thermometer, hygrometer, infrared temperature instrument, Air Quality Analysis device,
Air sense of movement answers ambient temperature data, humidity data, shell temperature data, air quality data, gas in device acquisition environment
Speed data is flowed, and the data of acquisition are transferred in categorised decision tree-model and carry out judgement processing, categorised decision tree-model root
Every environmental data is judged respectively according to preset environmental data range, so that corresponding regulating strategy is generated, by controlling
Processing system controls air-conditioning according to regulating strategy and executes corresponding operation, and finally realizes the automatic control of air-conditioning.
Embodiment two
As shown in Figure 1, a kind of air conditioner intelligent temperature control method based on Decision Tree Algorithm, including above-mentioned based on decision
The air conditioner intelligent temperature control system of tree classification algorithm, and specifically includes the following steps:
A. the preset comfortable environment number of human body sensory under normal circumstances in the categorised decision tree-model of control processing system
According to threshold range as categorised decision tree-model to the regulation threshold range of environmental data；Environmental data includes at least environment temperature
Degree evidence, humidity data, shell temperature data, air quality data, and/or air velocity data；
B. environmental data is acquired by information acquisition system and is transferred to control processing system as environmental data to be judged；
Wherein, when the environmental data of information acquisition system acquisition is transferred to control processing system, control processing system can be to the number received
According to progress data cleansing (rejecting dirty data), data analysis (deleting redundant data) and data conversion process, and will finally pass through
The data for meeting quality of data requirement of above-mentioned processing are transferred to categorised decision tree-model as environmental data to be judged；
C. it is treated in control processing system by categorised decision tree-model and judges that environmental data carries out judging processing and life
At corresponding regulating strategy；The threshold range for the environmental data that categorised decision tree-model is set in carries out Various types of data respectively
Discriminant classification processing, and generate corresponding regulating strategy；
D. control processing system controls air-conditioning according to regulating strategy and executes corresponding operation and to user feedback result.
Specifically, the data conversion process in step B is specially to seek data mean value processing, specifically include:
B1. information acquisition system acquires the environmental data in a detection cycle and is transferred to control processing system；One
Detection cycle is 60 seconds, and information acquisition system acquired an environmental data every 10 seconds；
B2. control processing system carries out average value to all kinds of environmental datas in i.e. 60s in the detection cycle received
It calculates, and the average value of all kinds of environmental datas obtained in one cycle is transferred to categorised decision tree-model as wait judge
Environmental data.
Such as in a detection cycle thermometer for obtain 6 secondary environment temperature be respectively as follows: 20.3 DEG C, 20.2 DEG C, 20.3 DEG C,
20.4 DEG C, 20.5 DEG C, 20.4 DEG C, then controlling processing system and averaging to 6 ambient temperature datas is 20.35 DEG C, i.e., actually
The environment temperature that incoming categorised decision tree-model is judged is 20.35 DEG C.
Wherein, as shown in Fig. 2, in the present embodiment, the generation step of the categorised decision tree-model in processing system is controlled such as
Under:
S101. it makes thorough investigation and study, counts the environmental data of environment where when people is comfortable on, environmental data at least wraps
Containing ambient temperature data, humidity data, shell temperature data, air quality data, air velocity data；
S102. statistics is carried out to the environmental data acquired in step S101 and manual sort is carried out to data, defined all kinds of
The range threshold of other environmental data, and a small number of rule progress dirty data cleaning treatments is obeyed according to most, it obtains relatively most
Representative training set and test data set；
S103. classifier is trained using training set obtained in step S102, and resulting to training with test data set
Classifier is tested, and categorised decision tree-model is obtained.
S104. the environmental data and other actual conditions (such as currently used geographical location) of the setting of user's habituation are combined
Beta pruning is carried out to obtained categorised decision tree and the range threshold of each classification data in categorised decision tree-model is optimized,
Obtain final optimal classification decision-tree model.
Specifically, when carrying out beta pruning processing to obtained categorised decision tree specifically, such as categorised decision in the present embodiment
Environmental data in tree-model only falls into 5 types i.e.: ambient temperature data, humidity data, shell temperature data, air quality number
According to, air velocity data, if environmental data is subdivided into 6 classes such as in the categorised decision tree-model counted according to big data: ring
Border temperature data, humidity data, shell temperature data, air quality data, air velocity data, oxygen content in air data, then
It needs to carry out rejecting processing to oxygen content in air data therein, so that the use that the function of air-conditioning is more bonded user needs
It asks.
Specifically, ambient temperature data regulation threshold range is environment temperature no more than T2, no in the step A of the present embodiment
Less than T1, it is that air humidity is not less than P1, is not more than P2 that humidity data, which regulates and controls threshold range, and shell temperature data regulate and control threshold value model
It encloses for shell temperature not less than ST1, no more than ST2, air quality data regulation threshold range is not more than for air quality index
AQI1, air velocity data regulation threshold range are that air velocity is not less than V1, is not more than V2.
As shown in figure 3, when wait judge that the ambient temperature data in environmental data is greater than T2 in the step C of the present embodiment
When, the regulating strategy control air-conditioning of categorised decision tree-model output carries out cooling processing, and environment temperature is at least reduced to T2,
When judging that the ambient temperature data in environmental data is less than T1, the regulating strategy of categorised decision tree-model output controls air-conditioning
Heating treatment is carried out, and environment temperature is at least increased to T1；
When judging that the air humidity data in environmental data are less than P1, the regulating strategy of categorised decision tree-model output
It controls air-conditioning and carries out humidification process, and air humidity is at least increased to P1, when wait judge the air humidity number in environmental data
When according to being greater than P2, the regulating strategy control air-conditioning of categorised decision tree-model output carries out dehumidification treatments, and at least by air humidity
It is reduced to P2；
When judging that the shell temperature data in environmental data are greater than ST2, the regulation plan of categorised decision tree-model output
Slightly control air-conditioning carries out cooling processing, and shell temperature data are at least reduced to ST2, when wait judge the body surface in environmental data
When temperature data is less than ST1, the regulating strategy control air-conditioning of categorised decision tree-model output carries out heating treatment, and at least by body
Table temperature data is increased to ST1；
When judging that the air quality index in environmental data is greater than AQI1, the regulation plan of categorised decision tree-model output
Slightly control air-conditioning carries out air cleaning, and air quality index is at least reduced to AQI1；
When judging that the air velocity data in environmental data are less than V1, the regulating strategy of categorised decision tree-model output
Control air-conditioning breezes up, and air velocity is at least increased to V1, when wait judge that the air velocity data in environmental data are big
When V2, the regulating strategy control air-conditioning of categorised decision tree-model output reduces wind-force, and air velocity is at least reduced to V2.
Preferably, the categorised decision tree-model of the present embodiment can also be achieved personalized customization and self-learning function, that is, divide
The regulation threshold range of environmental data in class decision-tree model can be more by user by user's sets itself or control processing system
The environmental data of secondary setting is as standard environment data and is set in the corresponding environmental data of substitution in categorised decision tree-model
Regulate and control threshold range.
Specifically, environmental data that user repeatedly sets as standard environment data and is set in point by control processing system
In class decision-tree model when the regulation threshold range of the corresponding environmental data of substitution specifically includes the following steps:
S1. i.e. acquisition user is multiple when the number that user continuously sets a certain environmental data to a certain fixed value is more than a times
The fixed value of the environmental data of sets itself；
S2. the standard value that the fixed value of the environmental data is placed in categorised decision tree-model and as the environmental data is replaced
For the regulation threshold range of corresponding environmental data.
Wherein, in the present embodiment in order to avoid there is user accidentally by causing the data information of mistake to be set to environment number
According to regulation threshold range, for every class environmental data be specifically set with regulation threshold value regulation threshold values up and down, specifically such as:
If the ambient temperature data regulation threshold range set in the present embodiment is not more than 28 DEG C as environment temperature, is not less than
18 DEG C, and the threshold values of regulation up and down of the regulation threshold value of ambient temperature data is 5 DEG C, even user wants sets itself by environment temperature
Regulation threshold range be increased to 40 DEG C, 40 DEG C with 28 DEG C of difference be 12 DEG C be more than ambient temperature data regulation threshold value
5 DEG C of threshold values of regulation up and down, then system inputs this time input for determining user for mistake, i.e., will not regulate and control ambient temperature data
Threshold range is set as 40 DEG C, and continues to keep original no more than 28 DEG C, the temperature range not less than 18 DEG C as environment temperature number
According to regulation threshold range.
It can be seen from the above content that the air conditioner intelligent temperature control of the invention based on Decision Tree Algorithm through the invention
System and method not only may make air-conditioning to have the function of automatically adjusting temperature, air-conditioning also may make to have self study and user
The function of personal settings is conducive to the satisfaction for improving product to improve the usage experience of user when the air conditioner is used.
It is understood that the principle that embodiment of above is intended to be merely illustrative of the present and the exemplary implementation that uses
Mode, however the present invention is not limited thereto.For those skilled in the art, essence of the invention is not being departed from
In the case where mind and essence, various changes and modifications can be made therein, these variations and modifications are also considered as protection scope of the present invention.
Claims (8)
1. the air conditioner intelligent temperature control system based on Decision Tree Algorithm, which is characterized in that including information acquisition system and control
Processing system, for the information acquisition system for acquiring environmental data, the environmental data includes at least ambient temperature data, wet
Degree evidence, shell temperature data, air quality data, and/or air velocity data；Classification is equipped in the control processing system
Decision-tree model, control processing system are connected with information acquisition system, and control processing system is used to acquire information acquisition system
Data be input in categorised decision tree-model and carry out classification processing, and controlled according to the classification results of categorised decision tree-model empty
It adjusts and executes corresponding operation.
2. the air conditioner intelligent temperature control system according to claim 1 based on Decision Tree Algorithm, which is characterized in that described
Information acquisition system includes at least thermometer, hygrometer, infrared temperature instrument, Air Quality Analysis device and/or air sense of movement
Answer device.
3. the air conditioner intelligent temperature control method based on Decision Tree Algorithm, which is characterized in that be based on including described in claim 1
The air conditioner intelligent temperature control system of Decision Tree Algorithm, and specifically includes the following steps:
A. the preset comfortable environmental data of human body sensory under normal circumstances in the categorised decision tree-model of control processing system
Threshold range is as categorised decision tree-model to the regulation threshold range of environmental data；The environmental data includes at least environment temperature
Degree evidence, humidity data, shell temperature data, air quality data, and/or air velocity data；
B. environmental data is acquired by information acquisition system and is transferred to control processing system as environmental data to be judged；
C. it is treated in control processing system by categorised decision tree-model and judges that environmental data carries out judging processing and generation pair
The regulating strategy answered；
D. control processing system controls air-conditioning according to regulating strategy and executes corresponding operation.
4. the air conditioner intelligent temperature control method according to claim 3 based on Decision Tree Algorithm, which is characterized in that described
Ambient temperature data regulation threshold range is that environment temperature is not more than T2, is not less than T1 in step A, and humidity data regulates and controls threshold value model
Enclose for air humidity not less than P1, no more than P2, shell temperature data regulate and control threshold range be shell temperature not less than ST1, no
Greater than ST2, it is air quality index no more than AQI1, air velocity data regulation threshold value that air quality data, which regulates and controls threshold range,
Range is that air velocity is not less than V1, is not more than V2.
5. the air conditioner intelligent temperature control method according to claim 4 based on Decision Tree Algorithm, which is characterized in that described
In step C when judging that the ambient temperature data in environmental data is greater than T2, the regulating strategy of categorised decision tree-model output
Control air-conditioning carries out cooling processing, and environment temperature is at least reduced to T2, when wait judge the environment temperature number in environmental data
When according to being less than T1, the regulating strategy control air-conditioning of categorised decision tree-model output carries out heating treatment, and at least by environment temperature
It is increased to T1；
When judging that the air humidity data in environmental data are less than P1, the regulating strategy control of categorised decision tree-model output
Air-conditioning carries out humidification process, and air humidity is at least increased to P1, when wait judge that the air humidity data in environmental data are big
When P2, the regulating strategy control air-conditioning of categorised decision tree-model output carries out dehumidification treatments, and at least reduces air humidity
To P2；
When judging that the shell temperature data in environmental data are greater than ST2, the regulating strategy control of categorised decision tree-model output
Air-conditioning processed carries out cooling processing, and shell temperature data are at least reduced to ST2, when wait judge the shell temperature in environmental data
When data are less than ST1, the regulating strategy control air-conditioning of categorised decision tree-model output carries out heating treatment, and at least by body surface temperature
Degree evidence is increased to ST1；
When judging that the air quality index in environmental data is greater than AQI1, the regulating strategy control of categorised decision tree-model output
Air-conditioning processed carries out air cleaning, and air quality index is at least reduced to AQI1；
When judging that the air velocity data in environmental data are less than V1, the regulating strategy control of categorised decision tree-model output
Air-conditioning breezes up, and air velocity is at least increased to V1, when wait judge that the air velocity data in environmental data are greater than V2
When, the regulating strategy control air-conditioning of categorised decision tree-model output reduces wind-force, and air velocity is at least reduced to V2.
6. the air conditioner intelligent temperature control method according to claim 4 based on Decision Tree Algorithm, which is characterized in that described
The environmental data that the regulation threshold range of environmental data can repeatedly be set user by user's sets itself or control processing system
The regulation threshold range of corresponding environmental data is substituted in categorised decision tree-model as standard environment data and being set in.
7. the air conditioner intelligent temperature control method according to claim 6 based on Decision Tree Algorithm, which is characterized in that described
The environmental data that user repeatedly sets as standard environment data and is set in categorised decision tree-model by control processing system
When substituting the regulation threshold range of corresponding environmental data specifically includes the following steps:
S1. i.e. acquisition user is repeatedly voluntarily when the number that user continuously sets a certain environmental data to a certain fixed value is more than a times
The fixed value of the environmental data of setting；
S2. the fixed value of the environmental data is placed in the substitution pair of the standard value in categorised decision tree-model and as the environmental data
The regulation threshold range for the environmental data answered.
8. the air conditioner intelligent temperature control method according to claim 3 based on Decision Tree Algorithm, which is characterized in that described
Step B specifically:
B1. information acquisition system acquires the environmental data in a detection cycle and is transferred to control processing system；It is one
Detection cycle is b seconds, and information acquisition system acquired an environmental data every c seconds, wherein b=c*n, n are not less than 1；
B2. processing system is controlled to all kinds of environmental datas progress mean value calculation in the detection cycle received, and will
The average value of all kinds of environmental datas in one cycle out is transferred to categorised decision tree-model as environmental data to be judged.
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| CN115031368A (en) * | 2022-06-29 | 2022-09-09 | 海信（广东）空调有限公司 | Air conditioner and control method thereof |
| CN115031373A (en) * | 2022-06-29 | 2022-09-09 | 海信（广东）空调有限公司 | Air conditioner and control method thereof |
| CN115059991A (en) * | 2022-06-29 | 2022-09-16 | 海信（广东）空调有限公司 | Air conditioner and control method thereof |
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