CN109028480B - Constant temperature and humidity control system and method thereof - Google Patents
Constant temperature and humidity control system and method thereof Download PDFInfo
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- CN109028480B CN109028480B CN201810587841.5A CN201810587841A CN109028480B CN 109028480 B CN109028480 B CN 109028480B CN 201810587841 A CN201810587841 A CN 201810587841A CN 109028480 B CN109028480 B CN 109028480B
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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
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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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
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
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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
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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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
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
- F24F2110/12—Temperature of the outside air
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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
- F24F2110/00—Control inputs relating to air properties
- F24F2110/20—Humidity
Abstract
The invention discloses a constant temperature and humidity control system, which comprises: the cloud server, the acquisition module and the control module are suitable for being in communication connection with the external Internet; the system comprises an acquisition module, a control module, a cloud server, a control module and an external Internet, wherein the acquisition module and the control module are respectively in communication connection with the cloud server, the acquisition module is used for detecting and collecting indoor temperature and humidity data and sending the indoor temperature and humidity data to the cloud server, the control module is used for controlling the working state of an indoor air conditioner, the cloud server is provided with a temperature and humidity prediction model, the temperature and humidity prediction model can combine current indoor temperature and humidity data from the acquisition module, control data from the control module and outdoor temperature data from the external Internet to predict the temperature and humidity change of the indoor environment, then different air conditioner operations are traversed according to prediction results, optimal air conditioner operation data for keeping indoor temperature and humidity constant are screened out from the optimal air conditioner operation data and sent to the control module to pre-control the indoor air conditioner in advance, and the indoor constant temperature and humidity are guaranteed.
Description
Technical Field
The invention relates to a constant temperature and humidity control system and a method thereof.
Background
In the conventional air conditioner in the prior art, the indoor temperature is adjusted by comparing the current indoor temperature with the temperature set by the user. The current indoor temperature is detected through the sensing element, then compared with the temperature set by the user, and corresponding control processing is carried out according to the comparison result. If the current indoor temperature has deviation from the set temperature, continuing to perform temperature regulation operation; and if the current indoor temperature does not have deviation from the set temperature, stopping the temperature regulation operation. The air conditioner can control and adjust the indoor temperature within a range that a human body feels comfortable, and the living standard of people is improved.
However, the conventional air conditioner control method has obvious defects. The indoor temperature is susceptible to interference from the outdoor environment. For example, after the outdoor temperature decreases in late nighttime, the indoor temperature is affected and decreases accordingly, and after the outdoor temperature increases in midday, the indoor temperature is affected and increases accordingly. Because the traditional air conditioner control mode simply depends on comparing the current indoor temperature with the set temperature to carry out temperature regulation operation, the regulation and control of the indoor temperature are lagged. The traditional air conditioner can carry out corresponding regulation and control only after detecting that the current temperature and the set temperature have obvious deviation, and can not really realize the constant temperature and humidity control of the indoor environment.
Disclosure of Invention
The invention aims to provide a constant temperature and humidity control system and a method thereof, which can accurately predict indoor temperature and humidity after a certain time, regulate and control the indoor temperature and humidity in advance and realize the constant temperature and humidity control of an indoor environment.
In order to achieve the above object, the present invention provides a constant temperature and humidity control system, comprising:
the cloud server is suitable for being in communication connection with the external Internet;
the device comprises an acquisition module and a control module; the collection module and the control module are respectively in communication connection with the cloud server, the collection module is used for detecting and collecting indoor temperature and humidity data and sending the indoor temperature and humidity data to the cloud server, the control module is suitable for being controllably connected to an indoor air conditioner and used for controlling the working state of the indoor air conditioner, the cloud server is provided with a temperature and humidity prediction model, the temperature and humidity prediction model can predict the temperature and humidity change of the indoor environment by combining the current indoor temperature and humidity data from the collection module, the control data from the control module and the outdoor temperature data from the external Internet, then different air conditioner operations are traversed according to the prediction result, the optimal air conditioner operation data for keeping the indoor constant temperature and humidity are screened out and sent to the control module, and therefore the advanced pre-control of the indoor air conditioner is realized, ensure that the indoor temperature and humidity are kept constant.
According to the preferred embodiment of the invention, the control module is configured to send newly generated control data to the cloud server at intervals of a preset time, and the control module is used for the cloud server to train the temperature and humidity prediction model according to the new control data, so that the prediction accuracy is improved.
According to a preferred embodiment of the present invention, the outdoor temperature data includes a current outdoor temperature, an outdoor temperature before a preset time period, and an outdoor temperature after the preset time period.
Preferably, the acquisition module is an SR3 sensor.
Preferably, the control module is an RM infrared remote controller.
According to another aspect of the present invention, the present invention further provides a constant temperature and humidity control method, which comprises the following steps:
(S1) acquiring current indoor temperature and humidity data, current indoor air conditioner control data, and outdoor temperature data;
(S2) inputting the current indoor temperature and humidity data, the current indoor air conditioner control data and the outdoor temperature data into a temperature and humidity prediction model, and predicting the change of the indoor temperature and humidity to obtain a prediction result;
(S3) traversing different air conditioner operations according to the prediction result, and screening out optimal air conditioner operation data for keeping the indoor temperature and humidity constant;
(S4) performing advanced pre-control of the indoor air conditioner according to the air conditioner optimal operation data.
According to a preferred embodiment of the present invention, the constant temperature and humidity control method further comprises: and (S5) training the temperature and humidity prediction model by using the newly generated air conditioner control data.
According to a preferred embodiment of the present invention, the outdoor temperature data includes a current outdoor temperature, an outdoor temperature before a preset time period, and an outdoor temperature after the preset time period.
According to a preferred embodiment of the present invention, the step (S5) further includes the steps of:
(S51) fixing a neural network model structure;
(S52) dividing the input temperature and humidity data into a training set and a test set;
(S53) randomly initializing values of weights and bias parameters in the neural network;
(S54) inputting the data of the training set into the neural network, performing linear and nonlinear operation of the full connection layer, and outputting a predicted value of the neural network;
(S55) calculating the error between the predicted value and the true value, performing reverse propagation to obtain the change quantity of each weight and bias parameter, and correcting the weight and bias parameter;
(S56) repeating the steps (S52) - (S55) until the error between the predicted value and the true value satisfies the preset threshold condition.
According to a preferred embodiment of the present invention, the step (S5) further includes: and (S57) changing the neural network model structure, repeating the steps (S52) to (S56), and selecting the model with the minimum error of the predicted values in all different neural network model structures for predicting the indoor temperature and humidity change.
Compared with the prior art, the invention has the beneficial effects that:
the indoor temperature and humidity environment change prediction can be realized according to the current indoor temperature and humidity data and by combining the outdoor temperature and the current control data of the indoor air conditioner, the indoor temperature and humidity are subjected to advanced pre-control adjustment according to the prediction result, and the indoor environment is kept at constant temperature and constant humidity.
The above and other objects, features, and advantages of the present invention will become further apparent from the following detailed description, the accompanying drawings, and the appended claims.
Drawings
FIG. 1 is a schematic configuration diagram in accordance with a preferred embodiment of the present invention;
FIG. 2 is a flow diagram of a method in accordance with a preferred embodiment of the present invention;
FIG. 3 is another method flow diagram in accordance with a preferred embodiment of the present invention;
in the figure: a cloud server 10; an acquisition module 20; a control module 30.
Detailed Description
The invention is further described with reference to the drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
The following description is presented to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art. The basic principles of the invention, as defined in the following description, may be applied to other embodiments, variations, modifications, equivalents, and other technical solutions without departing from the spirit and scope of the invention.
It will be understood by those skilled in the art that in the present disclosure, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for ease of description and simplicity of description, and do not indicate or imply that the referenced devices or components must be in a particular orientation, constructed and operated in a particular orientation, and thus the above terms are not to be construed as limiting the present invention.
It is understood that the terms "a" and "an" should be interpreted as meaning that a number of one element or element is one in one embodiment, while a number of other elements is one in another embodiment, and the terms "a" and "an" should not be interpreted as limiting the number.
Referring to fig. 1 to 3 of the drawings, a constant temperature and humidity control system and a method thereof according to a preferred embodiment of the present invention will be explained in the following description. The constant temperature and humidity control system provided by the invention can predict the temperature and humidity change of the indoor environment in advance according to the current indoor temperature and humidity data and by combining the outdoor temperature data and the current control data of the indoor air conditioner, and then pre-control and adjust the indoor air conditioner in advance according to the prediction result, so that the indoor environment is prevented from being interfered due to the change of the outdoor environment, and the indoor environment is kept at constant temperature and humidity.
Preferably, the outdoor temperature data includes a current outdoor temperature, an outdoor temperature before a preset time period, and an outdoor temperature after the preset time period.
Specifically, fig. 1 shows a schematic configuration diagram of a constant temperature and humidity control system according to a preferred embodiment of the present invention. The constant temperature and humidity control system comprises a cloud server 10 suitable for being in communication connection with the external Internet, an acquisition module 20 and a control module 30. The acquisition module 20 and the control module 30 are respectively in communication connection with the cloud server 10 through an electronic communication network. For example, the cloud server 10 may retrieve the parameters of the outdoor environment such as the current outdoor temperature, the previous outdoor temperature, and the next outdoor temperature from the external internet.
It is easily understood by those skilled in the art that the electronic communication network may be any electronic communication network that enables communication between the cloud server 10 and the control module 30 and the acquisition module 20, respectively. For example, the electronic communication network may be one of a Local Area Network (LAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), and the like. The electronic communication network may also be other communication networks capable of implementing the communication between the cloud server 10 and the control module 30, and the acquisition module 20, such as GSM, 3G mobile communication networks (CDMA, CDMA 200, TD-CDMA, WCDMA, etc.), 4G mobile communication networks (TD-LTE, FDD-LTE, etc.), 5G mobile communication networks, satellite communication, etc. In addition, the control module 30 and the acquisition module 20 may also communicate with the cloud server 10 by accessing to a Wireless Local Area Network (WLAN), a Bluetooth transmission network (Bluetooth) or a hotspot Point network (Hot Point), and then accessing or connecting to the electronic communication network through these wireless communication networks. Alternatively, the control module 30 and the acquisition module 20 may also communicate with the cloud server 10 through a preset custom communication data protocol.
The acquisition module 20 is configured to detect and collect indoor temperature and humidity data and send the collected indoor temperature and humidity data to the cloud server 10. The control module 30 is adapted to be controllably connected to the room air conditioner for controlling an operating state of the room air conditioner. The cloud server 10 is provided with a temperature and humidity prediction model, can predict indoor temperature and humidity changes, then traverses different air conditioner operations according to prediction results, screens out optimal air conditioner operation data keeping indoor temperature and humidity constant, sends the optimal air conditioner operation data to the control module 30, and performs advanced pre-control adjustment on the working state of the indoor air conditioner through the control module 30.
Preferably, the acquisition module 20 is an SR3 sensor.
Preferably, the control module 30 is an RM infrared remote controller.
More specifically, the cloud server 10 receives and combines the current indoor temperature and humidity data from the acquisition module 20, the control data for the indoor air conditioner from the control module 30, and the outdoor temperature data from the external internet, continuously trains the temperature and humidity prediction model by adjusting the model structure and the model parameters, selects the model structure with the minimum prediction error, and fixes the model parameters. The temperature and humidity prediction model can predict the temperature and humidity change of the indoor environment by combining the current indoor temperature and humidity data from the acquisition module 20, the control data from the control module 30 and the outdoor temperature data from the external internet, traverse different air conditioner operations according to the prediction result, screen out the optimal operation data of the air conditioner for keeping the indoor temperature and humidity constant, and send the optimal operation data to the control module 30. The control module 30 performs advanced pre-control adjustment on the indoor air conditioner according to the optimal operation data of the air conditioner, so that the indoor environment is kept at a constant temperature and humidity.
That is to say, the temperature and humidity prediction model can predict the indoor temperature and humidity after a certain time under the conditions of knowing the current indoor temperature and humidity, the current outdoor temperature, the previous integral point outdoor temperature, the next integral point outdoor temperature, the current air conditioner control data and the like, then traverse different air conditioner operations, and screen out the optimal air conditioner operation data for keeping the indoor temperature and humidity constant. For example, twelve o' clock at night currently, the outdoor temperature will decrease by 2 degrees after the cloud server 10 is called through the internet for 30 minutes, the temperature and humidity prediction model can predict the change of the indoor temperature and humidity after 30 minutes due to the interference of the external environment, then different air conditioner operations are traversed according to the prediction result, the optimal operation data of the air conditioner, which keeps the indoor temperature and humidity constant, is screened out from the optimal operation data and sent to the control module 30 to pre-control the indoor air conditioner in advance, so that the indoor temperature and humidity cannot be affected by the rapid decrease of the outdoor temperature after 30 minutes.
Preferably, the control module 30 is configured to send newly generated control data to the cloud server 10 at intervals of a preset time, so that the cloud server 10 trains the temperature and humidity prediction model according to the new control data, and accuracy of prediction is improved.
The conventional air conditioner in the prior art simply adjusts the working state of the air conditioner by comparing the deviation between the current indoor temperature and the set temperature, and the regulation and control of the indoor environment are delayed. Compared with the prior art, the constant temperature and humidity control system provided by the invention can predict the indoor temperature and humidity environment change according to the current indoor temperature and humidity data and by combining the outdoor temperature and the current air conditioner control data, and pre-control and adjust the indoor temperature and humidity in advance according to the prediction result, so that the indoor environment can be kept at constant temperature and humidity.
As shown in fig. 2, the present invention further provides a constant temperature and humidity control method, which comprises the following steps:
(S1) acquiring current indoor temperature and humidity data, current indoor air conditioner control data, and outdoor temperature data;
(S2) inputting the current indoor temperature and humidity data, the current indoor air conditioner control data and the outdoor temperature data into a temperature and humidity prediction model, and predicting the change of the indoor temperature and humidity to obtain a prediction result;
(S3) traversing different air conditioner operations according to the prediction result, and screening out optimal air conditioner operation data for keeping the indoor temperature and humidity constant;
(S4) performing advanced pre-control of the indoor air conditioner according to the air conditioner optimal operation data.
Preferably, the constant temperature and humidity control method further comprises: and (S5) training the temperature and humidity prediction model by utilizing newly generated air conditioner control data, so that the prediction accuracy is improved.
Preferably, the outdoor temperature data includes a current outdoor temperature, an outdoor temperature before a preset time period, and an outdoor temperature after the preset time period.
Specifically, as shown in fig. 3, the step (S5) further includes the steps of:
(S51) fixing a neural network model structure;
(S52) dividing the input temperature and humidity data into a training set and a test set;
(S53) randomly initializing values of weights and bias parameters in the neural network;
(S54) inputting the data of the training set into the neural network, performing linear and nonlinear operation of the full connection layer, and outputting a predicted value of the neural network;
(S55) calculating the error between the predicted value and the true value, performing reverse propagation to obtain the change quantity of each weight and bias parameter, and correcting the weight and bias parameter;
(S56) repeating the steps (S52) - (S55) until the error between the predicted value and the true value satisfies the preset threshold condition.
Preferably, the step (S5) further includes: and (S57) changing the neural network model structure, repeating the steps (S52) to (S56), and selecting the model with the minimum error of the predicted values in all different neural network model structures for predicting the indoor temperature and humidity change.
It will be appreciated by persons skilled in the art that the embodiments of the invention described above and shown in the drawings are given by way of example only and are not limiting of the invention. The objects of the invention have been fully and effectively accomplished. The functional and structural principles of the present invention have been shown and described in the examples, and any variations or modifications of the embodiments of the present invention may be made without departing from the principles.
Claims (7)
1. A constant temperature and humidity control system, comprising:
the cloud server is suitable for being in communication connection with the external Internet;
the device comprises an acquisition module and a control module; wherein the acquisition module and the control module are respectively in communication connection with the cloud server, the acquisition module is used for detecting and collecting indoor temperature and humidity data and sending the indoor temperature and humidity data to the cloud server, the control module is suitable for being controllably connected with an indoor air conditioner, used for controlling the working state of the indoor air conditioner, the cloud server is provided with a temperature and humidity prediction model, the temperature and humidity prediction model can predict the temperature and humidity change of the indoor environment by combining the current indoor temperature and humidity data from the acquisition module, the control data from the control module and the outdoor temperature data from the external Internet, then traversing different air conditioner operations according to the prediction result, screening out the optimal operation data of the air conditioner keeping the indoor temperature and humidity constant from the operation data and sending the optimal operation data to the control module, the control module carries out advanced pre-control on the indoor air conditioner according to the optimal operation data of the air conditioner; the outdoor temperature data includes a current outdoor temperature, an outdoor temperature before a preset time period, and an outdoor temperature after the preset time period.
2. The system according to claim 1, wherein the control module is configured to send newly generated control data to the cloud server at predetermined intervals, so that the cloud server trains the temperature and humidity prediction model according to the new control data.
3. The constant temperature and humidity control system as claimed in any one of claims 1-2, wherein the collection module is an SR3 sensor, and the control module is an RM infrared remote controller.
4. A constant temperature and humidity control method is characterized by comprising the following steps:
(S1) acquiring current indoor temperature and humidity data, current indoor air conditioner control data, and outdoor temperature data;
(S2) inputting the current indoor temperature and humidity data, the current indoor air conditioner control data and the outdoor temperature data into a temperature and humidity prediction model, and predicting the change of the indoor temperature and humidity to obtain a prediction result; the outdoor temperature data comprises the current outdoor temperature, the outdoor temperature before the preset time period and the outdoor temperature after the preset time period;
(S3) traversing different air conditioner operations according to the prediction result, and screening out optimal air conditioner operation data for keeping the indoor temperature and humidity constant;
(S4) performing advanced pre-control of the indoor air conditioner according to the air conditioner optimal operation data.
5. The method of claim 4, further comprising: and (S5) training the temperature and humidity prediction model by using the newly generated air conditioner control data.
6. The constant temperature and humidity control method according to claim 5, wherein the step (S5) further comprises the steps of:
(S51) fixing a neural network model structure;
(S52) dividing the input temperature and humidity data into a training set and a test set;
(S53) randomly initializing values of weights and bias parameters in the neural network;
(S54) inputting the data of the training set into the neural network, performing linear and nonlinear operation of the full connection layer, and outputting a predicted value of the neural network;
(S55) calculating the error between the predicted value and the true value, performing reverse propagation to obtain the change quantity of each weight and bias parameter, and correcting the weight and bias parameter;
(S56) repeating the steps (S52) - (S55) until the error between the predicted value and the true value satisfies the preset threshold condition.
7. The constant temperature and humidity control method according to claim 6, wherein the step (S5) further comprises: and (S57) changing the neural network model structure, repeating the steps (S52) to (S56), and selecting the model with the minimum error of the predicted values in all different neural network model structures for predicting the indoor temperature and humidity change.
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| CN110082979B (en) * | 2019-03-19 | 2022-02-08 | 中国科学院自动化研究所 | Method and device for adjusting transparency of vehicle glass |
| CN109945439A (en) * | 2019-03-29 | 2019-06-28 | 龙马智芯（珠海横琴）科技有限公司 | A kind of indoor environment parameter control method and system |
| CN110135656A (en) * | 2019-05-27 | 2019-08-16 | 中国科学院自动化研究所 | Intelligent adjusting method, system, the device of electrochomeric glass for building |
| WO2020237668A1 (en) * | 2019-05-31 | 2020-12-03 | 亿可能源科技（上海）有限公司 | Air-conditioning system management method, air-conditioning system control method, storage medium and control platform |
| CN110454923A (en) * | 2019-09-03 | 2019-11-15 | 广州原典装饰设计有限公司 | A kind of intelligence room temperature regulation system |
| CN110986249B (en) * | 2019-11-07 | 2021-09-24 | 格力电器（杭州）有限公司 | Self-adjustment control method and system of air conditioner and air conditioner |
| CN112484259B (en) * | 2020-12-04 | 2021-11-16 | 珠海格力电器股份有限公司 | Humidity control method and device, electronic equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101825327A (en) * | 2010-05-28 | 2010-09-08 | 哈尔滨工业大学 | Method for acquiring optimum air-conditioning system operation parameters based on weather forecast |
| CN105387565A (en) * | 2015-11-24 | 2016-03-09 | 深圳市酷开网络科技有限公司 | Temperature adjusting method and device |
| CN107730087A (en) * | 2017-09-20 | 2018-02-23 | 平安科技（深圳）有限公司 | Forecast model training method, data monitoring method, device, equipment and medium |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102563808B (en) * | 2012-01-11 | 2014-02-26 | 华南理工大学 | Automatic control method of indoor environment comfort level |
| US9460404B2 (en) * | 2013-07-10 | 2016-10-04 | Scentair Technologies, Llc | Scent delivery system scheduling |
| CN104374053B (en) * | 2014-11-25 | 2017-02-22 | 珠海格力电器股份有限公司 | Intelligent control method, device and system |
| JP2017003192A (en) * | 2015-06-10 | 2017-01-05 | 株式会社東芝 | Energy management device, energy management method and energy management program |
| CN106322656B (en) * | 2016-08-23 | 2019-05-14 | 海信（山东）空调有限公司 | A kind of air conditioning control method and server and air-conditioning system |
-
2018
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101825327A (en) * | 2010-05-28 | 2010-09-08 | 哈尔滨工业大学 | Method for acquiring optimum air-conditioning system operation parameters based on weather forecast |
| CN105387565A (en) * | 2015-11-24 | 2016-03-09 | 深圳市酷开网络科技有限公司 | Temperature adjusting method and device |
| CN107730087A (en) * | 2017-09-20 | 2018-02-23 | 平安科技（深圳）有限公司 | Forecast model training method, data monitoring method, device, equipment and medium |
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Address after: 310051 Room 101, 1st Floor, Block C, No. 57, Changhe Street, Binjiang District, Hangzhou City, Zhejiang Province Applicant after: Hangzhou Bolian Intelligent Technology Co., Ltd. Address before: 310051 Room 106, Building No. 1, 611 Jianghong Road, Changhe Street, Binjiang District, Hangzhou City, Zhejiang Province Applicant before: Hangzhou Gubei Electronic Technology Co., Ltd. |
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