CN107504656B - A kind of air conditioner Learning Control Method and system - Google Patents
A kind of air conditioner Learning Control Method and system Download PDFInfo
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- CN107504656B CN107504656B CN201710834320.0A CN201710834320A CN107504656B CN 107504656 B CN107504656 B CN 107504656B CN 201710834320 A CN201710834320 A CN 201710834320A CN 107504656 B CN107504656 B CN 107504656B
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Abstract
The invention discloses a kind of air conditioner Learning Control Method and systems.The air conditioner automatic learning control system includes an information acquisition module and an automatic control module, wherein：Described information acquisition module acquisition user is turned on or off the data of air conditioner using remote controler or APP, and is sent to the automatic control module；The automatic control module carries out analyzing processing by the switching on and shutting down custom of self study user to the data of acquisition, identifies the switching on and shutting down period of air conditioner；The automatic control module is respectively handled the switching on and shutting down period of air conditioner, determines the switching on and shutting down time of air conditioner；The automatic control module carries out automatically controlling the switching on and shutting down time of air conditioner.Behavioural habits of the present invention according to user, predict the unused time of air-conditioning, it can be achieved that air conditioner intelligentized control method.
Description
Technical field
The present invention relates to air-conditioning technical field, more particularly to a kind of air conditioner Learning Control Method and system.
Background technology
Use for air conditioner, most people all follow simple repeat pattern, such as torridity summer, air conditioner user
Common refrigeration mode after get up in the morning, opens air-conditioning, leaves home to close air-conditioning when working, comes off duty go back home at night, can be again turned on
Air-conditioning can close air-conditioning, or set air-conditioning to timing shutdown before sleep.All it is above using biography to the control majority of air-conditioning
The control method of system controls air-conditioning by the button on manual manipulation remote controler.
However, there are inconveniences for the method for this control air-conditioning, it is that the open and close repeated is brought very to user first
It is big inconvenient, moreover, sometimes, when user goes to work hastily, often forgetting to close air-conditioning, causing waste of energy.Secondly, pass through
Manual manipulation remote controler presses the button in remote control to realizing the control of each function of air-conditioning, to lack intelligence, can not achieve
It automatically controls.
It is counted according to scientific research, although there is a few peoples' behavioral activity irregular, most people follows simple repetition
Pattern.One is published in《Science》It is on magazine the study found that 93% human behavior is foreseeable, prediction mode is root
According to following content of the act of the action trail prediction individual before individual.Based on this, and following all mechanical equipments will be towards
Artificial intelligence direction is developed, therefore, it is necessary to a kind of scheme of air-conditioning Learning Control Method of developmental research is carried out, to realize air-conditioning
It is intelligent so that air-conditioning can allow air-conditioning virtually being brought more to user by the use habit of continuous self study user
The experience of comfortable air temperature modification.
Invention content
To solve existing technical problem, a kind of air conditioner Learning Control Method of present invention proposition and system, with
The intelligence of air-conditioning is improved, the comfort that user uses air-conditioning is improved, air-conditioning is allowed virtually to bring more comfortable sky to user
The experience that temperature degree is adjusted.
In order to achieve the above objectives, the technical solution of the embodiment of the present invention is realized in：
A kind of air conditioner Learning Control Method, including an information acquisition module and an automatic control module, the self study
Control method includes the following steps：
Step S10：Described information acquisition module acquisition user is turned on or off the number of air conditioner using remote controler or APP
According to, and the data of acquisition are sent to the automatic control module；
Step S11：The automatic control module carries out at analysis the data of acquisition by the switching on and shutting down custom of self study user
Reason, identifies the switching on and shutting down period of air conditioner；
Step S12：The automatic control module is respectively handled the switching on and shutting down period of air conditioner, determines opening for air conditioner
It shuts down the moment；
Step S13：The automatic control module carries out automatically controlling the switching on and shutting down time of air conditioner.
In one embodiment, server beyond the clouds, the data of described information acquisition module acquisition are arranged in the automatic control module
Be sent to the automatic control module of cloud server by a communication module, the automatic module by real-time performance to air conditioner from
Dynamic control.
The data acquired in step S10 include time data and weather data, when the time data is defined as the date
Every minute and second, the weather data are defined as：Period/weather condition/outdoor environment temperature/outdoor air relative humidity/outdoor is empty
Makings amount.
Identify that the available machine time section of air conditioner includes in the step S11：
Step S1100. defines the available machine time sensitive factor of air conditioner；
Step S1101. is as unit of 10 days, record ith booting moment Ton-i；
Step S1102. was divided into 24 hour periods by one day, and recorded the period residing for the booting moment；
Step S1103. is within 10 day period, respectively to available machine time sensitive factor γ in 24 hour periodBootingSummation,
It is denoted as the n-th hour period：∑γBe switched on n(24 hour period of n 1,2,3 ...)；
Step S1104. is within 10 day period, to the time-sensitive factor gamma that is switched onBootingSummation, is denoted as：∑γBe switched on i(i is
Be switched on number)；
Step S1105. when meeting the following conditions simultaneously, then it is assumed that n-th hour is available machine time section：
(1)∑γBe switched on n/∑γBe switched on i>=a1%；
It is switched on number of days >=d1 days in the n-th period in (2) 10 days；
(3) indoor circumstance temperature >=Tc1 degree.
Identify that the unused time section of air conditioner includes in the step S11：
Step 1106. defines the unused time sensitive factor of air conditioner；
Step 1107. is as unit of 10 days, record ith shutdown moment Toff-i；
Step 1108. was divided into 24 hour periods by one day, and recorded the period residing for the shutdown moment；
Step 1109. is within 10 day period, respectively to machine time-sensitive factor gamma of shutting down in 24 small periodsShutdownSummation, note
For m hour periods：∑γBe switched on m(24 hour period of m 1,2,3 ...)；
Step 1110 is within 10 day period, to the time-sensitive factor gamma that is switched onShutdownSummation, is denoted as ∑ γShut down i(i is shutdown
Number)；
Step 1111. when meeting the following conditions simultaneously, then it is assumed that m hours are unused time section：
(1)∑γShut down m/∑γShut down i>=a2%；
It shuts down number of days >=d2 days in the m periods in (2) 10 days；
(3) indoor circumstance temperature≤Tc2 degree.
Determine that the available machine time of air conditioner includes in the step S12：The booting in all available machine time sections is recorded respectively
Time ton-n-i calculates the self study available machine time of the n-th hour period,
Wherein,
Indicate that self study available machine time, unit are：1min；
ton-n-iIndicate that the practical available machine time in the n-th available machine time section, unit are：1min；
Timen-onIndicate the booting total degree in n-th hour available machine time section in 10 days.
Determine that the unused time of air conditioner includes in the step S12：The shutdown in all unused time sections is recorded respectively
Time toff-m-i, the self study unused time of m hour periods is calculated,
Wherein：
Indicate that the self study unused time calculated, unit are：1min；
toff-m-iIndicate that the actually powered off time in m unused time section, unit are：1min；
Timem-offIndicate the shutdown total degree in m hours unused time section in 10 days.
Step S13 includes directly controlling the switching on and shutting down of air conditioner, or by APP pushed informations, remind user's switching on and shutting down.
The present invention also proposes a kind of air conditioner automatic learning control system, including an information acquisition module and an automatic control module,
It is characterized in that：
Described information acquisition module acquisition user is turned on or off the data of air conditioner using remote controler or APP, concurrently
It is sent to the automatic control module；
The automatic control module carries out analyzing processing by the switching on and shutting down custom of self study user to the data of acquisition, identifies
The switching on and shutting down period of air conditioner；
The automatic control module is respectively handled the switching on and shutting down period of air conditioner, when determining the switching on and shutting down of air conditioner
Between；
The automatic control module carries out automatically controlling the switching on and shutting down time of air conditioner.
In one embodiment, server beyond the clouds, the data of described information acquisition module acquisition are arranged in the automatic control module
Be sent to the automatic control module of cloud server by a communication module, the automatic module by real-time performance to air conditioner from
Dynamic control.
The advantageous effect of technical solution of the present invention is：
Behavioural habits of the present invention according to user, predict the unused time of air-conditioning, it can be achieved that air conditioner intelligent, can pass through
The use habit of continuous self study user, allows air-conditioning in the body for virtually bringing more comfortable air temperature modification to user
It tests, improves the comfort that user uses air-conditioning.
Description of the drawings
Fig. 1 is the flow chart of air conditioner Learning Control Method of the present invention.
Fig. 2 is the schematic diagram of one embodiment of air conditioner automatic learning control system of the present invention.
Fig. 3 is the flow chart for the available machine time section for identifying air conditioner.
Fig. 4 is the flow chart for the unused time section for identifying air conditioner.
Specific implementation mode
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction with the embodiment of the present invention and attached
Figure, is described in detail technical solution of the present invention.
Air conditioner Learning Control Method of the present invention passes through continuous self study user according to the behavioural habits before user
Use habit, carry out self study, predict the switching on and shutting down time of air-conditioning, to improve air conditioner intelligent, realize air conditioner intelligent,
It is brought convenience for user.
Air conditioner automatic learning control system proposed by the present invention includes an information acquisition module and an automatic control module.Such as Fig. 1
Shown, air conditioner Learning Control Method proposed by the present invention includes the following steps：
Step S10：Described information acquisition module acquisition user is turned on or off the number of air conditioner using remote controler or APP
According to, and automatic control module is sent to by communication module.
Fig. 2 is the schematic diagram of one embodiment of the invention, and in the embodiment, automatic control module is placed on high in the clouds, information acquisition module
User is acquired to the use habit data of air conditioner operation, and by with communication module, such as will use by the internets family wifi
The data that family is turned on or off air-conditioning upload to cloud server, service carry out processing analysis to data beyond the clouds, through processing
The switching on and shutting down time analyzed will control being turned on or off for air-conditioning.
The data of acquisition include time data and weather data.The input of time data includes the following steps：
Air-conditioner set is connect with APP client networks, the synchronizing network time；Wherein, the information of time includes the date
Hour Minute Second, xx divides xx seconds when time data format is xxxx xx month xx day xx.
Specifically, air-conditioner set synchronized the primary network time at interval of 24 hours using random process；APP clients according to
The mobile phone default setting synchronizing network time.
The input of the weather data includes：With the weather of air-conditioner set position Weather information as input, tool
Body includes：The information such as period, weather condition, outdoor environment temperature, outdoor air relative humidity and Outdoor Air Quality.This
In inventive embodiments, the format of weather data is：Period/weather condition/outdoor environment temperature/outdoor air relative humidity/
Outdoor Air Quality, such as：16:00-17:00/ sunny/30 DEG C/96%/excellent.
Step S11：Automatic control module carries out analyzing processing by the switching on and shutting down custom of self study user to the data of acquisition, knows
Do not go out the switching on and shutting down period of air conditioner.
Specifically comprise the following steps：
Step S1100：Define the switching on and shutting down time-sensitive factor.Big data statistics is carried out according to the use habit to user,
Wherein, the period of air-conditioning is often used in user, the time-sensitive factor is high, and the period for the air-conditioning that is of little use in user, time are quick
It is small to feel the factor, and the time-sensitive factor at weekend is slightly above the time-sensitive factor of the week.In the embodiment of the present invention,
The switching on and shutting down time-sensitive factor of every 1 hour period is defined as follows shown in table 1 in 24 hours.
1 switching on and shutting down time-sensitive factor gamma of table
Step S1101：As unit of 10 days, record ith booting moment Ton-I。
From first day 00:00 started, by the 10th day 23:At 59 moment, the record ith booting moment is Ton-i。
Step S1102：It was divided into 24 hour periods by one day, and records the period residing for the booting moment；
Specifically, it was divided into 24 hour periods by one day, and records the period residing for the booting moment.After 10 days full,
An available machine time section is updated according to window mode is drawn within every 1 day.After reaching 10 days, the 11st day data are exactly the data on the addition same day
And remove first day data of current file leader, it is exactly the data on the addition same day within the 12nd day, and remove first day number of current file leader
According to holding only stores 10 days data, updates within every 1 day an available machine time section in this way.In the present embodiment for 10 days,
Certainly, 10 days are not merely limited to.
Step S1103：Within 10 day period, respectively to available machine time sensitive factor γ in 24 hour periodBootingSummation,
It is denoted as the n-th hour period：∑γBe switched on n(24 hour period of n 1,2,3 ...).
Step S1104：Within 10 day period, to the time-sensitive factor gamma that is switched onBootingSummation, is denoted as：∑γBe switched on i(i is
Be switched on number).
Step S1105：When meeting the following conditions simultaneously, then it is assumed that n-th hour is available machine time section：
(1)∑γBe switched on n/∑γBe switched on i≥a1；
In (2) 10 days the n-th period booting number of days >=d1 days；
(3) interior circumstance temperature >=Tc1 (circumstance temperature≤T in room when heatingh1)
Wherein, 15%≤a1≤25% (unit：Percentage)；
4≤d1≤6 (unit：Number of days)；
20℃≤Tc1≤26℃；
10℃≤Th1≤15℃；
It is possible that section of multiple available machine times in 24 hours one day.If available machine time section is adjacent, available machine time section
Merge, it is believed that this time adjacent segments is user's available machine time section.
Identify that the unused time section of air conditioner includes in the step S11：
Step 1106：Define the switching on and shutting down time-sensitive factor of air conditioner；
Step 1107：As unit of 10 days, record ith shutdown moment Toff-i；
Specifically, from first day 00:00 started, by the 10th day 23:At 59 moment, the record ith shutdown moment is Toff-i。
Step 1108：It was divided into 24 hour periods by one day, and records the period residing for the shutdown moment；Specifically,
It was divided into 24 hour periods by one day, and records the period residing for the shutdown moment, after 10 days full, every 1 day according to a stroke window side
Formula updates a unused time section.After reaching 10 days, the 11st day data are exactly the data on the addition same day and remove current file leader
First day data is exactly the data on the addition same day on the 12nd day, and removes first day data of current file leader, keeps only storage 10
It data update a unused time section for every 1 day in this way.In the present embodiment for 10 days, certainly, not merely limit
It is scheduled on 10 days.
Step 1109：Within 10 day period, respectively to machine time-sensitive factor gamma of shutting down in 24 small periodsShutdownSummation, note
For m hour periods：∑γBe switched on m(24 hour period of m 1,2,3 ...)；
Step 1110：Within 10 day period, to the time-sensitive factor gamma that is switched onShutdownSummation, is denoted as ∑ γShut down i(i is to close
Machine number)
Step 1111：When meeting the following conditions simultaneously, then it is assumed that m hours are unused time section：
(1)∑γShut down m/∑γShut down i≥a2；
It shuts down number of days >=d2 in the m periods in (2) 10 days；
(3) interior circumstance temperature≤Tc2 (when heating >=Th2)
Wherein：15%≤a2≤25% (percentage)；
4≤d2≤6 (number of days)；
26℃≤Tc2≤29℃；(temperature)
5℃≤Th1≤10℃；
It is possible that section of multiple unused time in 24 hours one day.If unused time section is adjacent, unused time section
Merge, it is believed that this time adjacent segments be when the user turns it down between section.
Step S12：Automatic control module is respectively handled the switching on and shutting down period of air conditioner, determines the switching on and shutting down of air conditioner
Time.
The available machine time is calculated, records the available machine time t in all available machine time sections respectivelyon-n-i, calculate n-th hour time
The self study available machine time of section.
From first day 00:00 started, by the 10th day 23:59 moment terminated, and updated a self study available machine time.It is 10 days full
Afterwards, the 11st day data are exactly the data on the addition same day and remove first day data of current file leader, and the 12nd day is exactly that addition is worked as
It data, and remove first day data of current file leader, the data of only storage 10 days are kept, update one in this way within every 1 day
The secondary self study available machine time.In the present embodiment for 10 days, certainly, it is not merely limited to 10 days.
The self study available machine time：
Wherein：
Indicate that self study available machine time, unit are：1min；
ton-n-iIndicate that the practical available machine time in the n-th available machine time section, unit are：1min；
Timen-onIndicate the booting total degree in n-th hour available machine time section in 10 days.
Self study is arrivedTime, 30min obtains the outdoor weather situation where air-conditioning before booting, if refrigeration mode
Under, outdoor temperature >=TWeather1, outdoor temperature≤T under heating modeWeather2；Then be switched on operation.
25℃≤TWeather1；
TWeather2≤15℃；
The unused time is calculated, records the unused time t in all unused time sections respectivelyoff-m-i, calculate m hours time
The self study unused time of section.
From first day 00:00 started, by the 10th day 23:59 moment terminated, and updated a self study unused time.It is 10 days full
Afterwards, the 11st day data are exactly the data on the addition same day and remove first day data of current file leader, and the 12nd day is exactly that addition is worked as
It data, and remove first day data of current file leader, the data of only storage 10 days are kept, update one in this way within every 1 day
The secondary self study unused time.In the present embodiment for 10 days, certainly, it is not merely limited to 10 days.
The self study unused time：
Wherein：
Indicate that the self study unused time calculated, unit are：1min；
toff-m-iIndicate that the actually powered off time in m unused time section, unit are：1min；
Timem-offIndicate the shutdown total degree in m hours unused time section in 10 days.
Self study is arrivedTime then shuts down to air-conditioning at the moment.If this period air-conditioning is in the power-offstate,
Then without processing.
Step S13：Cloud server carries out automatically controlling the switching on and shutting down time of air conditioner.
After the switching on and shutting down time calculates, it can directly be turned on or off air-conditioning at the time point calculated.Certainly,
The switching on and shutting down time advance calculated can also be pushed to user APP, be decided whether to be turned on or off air-conditioning by user.
If user receives the message of the secondary prompting, it is turned on or off air-conditioning, if user does not receive the secondary prompting message, to air-conditioning
Device is without control.
In the embodiment of the present invention, the factor in switching on and shutting down time-sensitive factor table is a kind of optimal form, other according to
This method changes factor value, also in the scope of the present invention.Period used in the embodiment of the present invention is to retouch
It states more specifically, using other similar methods time by stages, also in protection domain.According to one in the embodiment of the present invention
It for 24 hours the period come by stages, can also come time subregion per half an hour, or per quarter.
Air conditioner automatic learning control system proposed by the present invention, including the information collection mould that is arranged on air conditioner mainboard
Block and an automatic control module, automatic control module can be located on air conditioner mainboard, can also be arranged on server beyond the clouds, latter feelings
Condition information acquisition module passes through the automatic control module communication on a communication module and cloud server.In the embodiment shown in Figure 2,
Information acquisition module acquisition user is turned on or off the data of air conditioner using remote controler or APP, and by communication module
Pass to the automatic control module on cloud server.Automatic control module carries out the data of acquisition by the switching on and shutting down custom of self study user
Analyzing processing identifies the switching on and shutting down period of air conditioner and the switching on and shutting down time and is carried out to the switching on and shutting down time of air conditioner automatic
Control.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent replacement, improvement and so on should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of air conditioner Learning Control Method, which is characterized in that described including an information acquisition module and an automatic control module
Learning Control Method include the following steps：
Step S10：Described information acquisition module acquisition user is turned on or off the data of air conditioner using remote controler or APP,
And the data of acquisition are sent to the automatic control module；
Step S11：The automatic control module carries out analyzing processing by the switching on and shutting down custom of self study user to the data of acquisition, knows
Do not go out the switching on and shutting down period of air conditioner；
Step S12：The automatic control module is respectively handled the switching on and shutting down period of air conditioner, determines the switching on and shutting down of air conditioner
Moment, wherein determine that the available machine time of air conditioner includes：The available machine time t in all available machine time sections is recorded respectivelyon-n-i, meter
The self study available machine time of the n-th hour period is calculated,
Wherein：Indicate that self study available machine time, unit are：1min, ton-n-iIndicate actually opening in the n-th available machine time section
Machine time, unit are：1min, Timen-onIndicate the booting total degree in n-th hour available machine time section in 10 days；
Determine that the unused time of air conditioner includes：The unused time t in all unused time sections is recorded respectivelyoff-m-i, calculate m
The self study unused time of hour period,
Wherein：Indicate that the self study unused time calculated, unit are：1min, toff-m-iIt indicates in m unused time section
Actually powered off time, unit are：1min, Timem-offIndicate the shutdown total degree in m hours unused time section in 10 days；
Step S13：The automatic control module according to switching on and shutting down moment of the determining air conditioner to switching on and shutting down time of air conditioner into
Row automatically controls.
2. air conditioner Learning Control Method according to claim 1, which is characterized in that the automatic control module is arranged in cloud
Server, the data of described information acquisition module acquisition is held to be sent to the automatic control mould on cloud server by a communication module
Block, the automatic module automatically control air conditioner by real-time performance.
3. air conditioner Learning Control Method according to claim 1 or 2, which is characterized in that the number acquired in step S10
According to including time data and weather data, the time data is defined as date Hour Minute Second, and the weather data is defined as：When
Between section/weather condition/outdoor environment temperature/outdoor air relative humidity/Outdoor Air Quality.
4. air conditioner Learning Control Method according to claim 1 or 2, which is characterized in that identified in the step S11
Go out air conditioner available machine time section include：
Step S1100. defines the available machine time sensitive factor of air conditioner；
Step S1101. is as unit of 10 days, record ith booting moment Ton-i；
Step S1102. was divided into 24 hour periods by one day, and recorded the period residing for the booting moment；
Step S1103. is within 10 day period, respectively to available machine time sensitive factor γ in 24 hour periodBootingSummation, is denoted as
N-th hour period：∑γ bootings n(24 hour period of n 1,2,3 ...)；
Step S1104. is within 10 day period, to the time-sensitive factor gamma that is switched onBootingSummation, is denoted as：∑γ bootings i(i is booting time
Number)；
Step S1105. when meeting the following conditions simultaneously, then it is assumed that n-th hour is available machine time section：
(1)∑γBe switched on n/∑γ bootings i>=a1%；
It is switched on number of days >=d1 days in the n-th period in (2) 10 days；
(3) indoor circumstance temperature >=Tc1 degree.
5. air conditioner Learning Control Method according to claim 1 or 2, which is characterized in that identified in the step S11
Go out air conditioner unused time section include：
Step 1106. defines the unused time sensitive factor of air conditioner；
Step 1107. is as unit of 10 days, record ith shutdown moment Toff-i；
Step 1108. was divided into 24 hour periods by one day, and recorded the period residing for the shutdown moment；
Step 1109. is within 10 day period, respectively to machine time-sensitive factor gamma of shutting down in 24 small periodsShutdownSummation is denoted as the
M hour periods：∑γBe switched on m(24 hour period of m 1,2,3 ...)；
Step 1110 is within 10 day period, to the time-sensitive factor gamma that is switched onShutdownSummation, is denoted as ∑ γShut down i(i is shutdown time
Number)；
Step 1111. when meeting the following conditions simultaneously, then it is assumed that m hours are unused time section：
(1)∑γShut down m/∑γShut down i>=a2%；
It shuts down number of days >=d2 days in the m periods in (2) 10 days；
(3) indoor circumstance temperature≤Tc2 degree.
6. air conditioner Learning Control Method according to claim 4, which is characterized in that step 1101 includes 10 days full
Afterwards, an available machine time section is updated according to window mode is drawn within every 1 day.
7. air conditioner Learning Control Method according to claim 5, which is characterized in that step 1107 includes 10 days full
Afterwards, a unused time section is updated according to window mode is drawn within every 1 day.
8. air conditioner Learning Control Method according to claim 1 or 2, which is characterized in that step S13 includes directly controlling
The switching on and shutting down of air conditioner processed, or by APP pushed informations, remind user's switching on and shutting down.
9. a kind of air conditioner automatic learning control system, including an information acquisition module and an automatic control module, it is characterised in that：
Described information acquisition module acquisition user is turned on or off the data of air conditioner using remote controler or APP, and is sent to
The automatic control module；
The automatic control module carries out analyzing processing by the switching on and shutting down custom of self study user to the data of acquisition, identifies air-conditioning
The switching on and shutting down period of device；
The automatic control module is respectively handled the switching on and shutting down period of air conditioner, determines the switching on and shutting down time of air conditioner；Its
In, determine that the available machine time of air conditioner includes：The available machine time t in all available machine time sections is recorded respectivelyon-n-i, it is small to calculate n-th
When the period the self study available machine time,
Wherein：Indicate that self study available machine time, unit are：1min, ton-n-iIndicate actually opening in the n-th available machine time section
Machine time, unit are：1min, Timen-onIndicate the booting total degree in n-th hour available machine time section in 10 days；
Determine that the unused time of air conditioner includes：The unused time t in all unused time sections is recorded respectivelyoff-m-i, calculate m
The self study unused time of hour period,
Wherein：Indicate that the self study unused time calculated, unit are：1min, toff-m-iIt indicates in m unused time section
Actually powered off time, unit are：1min, Timem-offIndicate the shutdown total degree in m hours unused time section in 10 days；
The automatic control module carries out automatically controlling the switching on and shutting down time of air conditioner.
10. air conditioner automatic learning control system as claimed in claim 9, which is characterized in that the automatic control module is arranged in cloud
Server, the data of described information acquisition module acquisition is held to be sent to the automatic control module of cloud server by a communication module,
The automatic module automatically controls air conditioner by real-time performance.
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| KR102026020B1 (en) | 2018-04-10 | 2019-11-26 | 엘지전자 주식회사 | Air-conditioner based on parameter learning using artificial intelligence, cloud server, and method of operating and controlling thereof |
| CN108826595A (en) * | 2018-04-26 | 2018-11-16 | 上海康斐信息技术有限公司 | A kind of control method and system of air purifier |
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