Comfortable state evaluation method, device and equipment of air conditioner and storage medium

Abstract

The invention relates to the technical field of air conditioners, in particular to a comfort state evaluation method, device and equipment of an air conditioner and a storage medium. Multiple pieces of operation data during operation of the air conditioner are collected, and the distribution distance between the operation data of each air conditioner and user box separation data is calculated; the technical problem that in the prior art, the comfort evaluation accuracy is not high when a user uses the air conditioner is solved, and the comfort evaluation accuracy is improved by generating the comfort index according to the distribution distance to improve the anti-interference performance of comfort evaluation and finally evaluating the comfort state of the air conditioner according to the comfort index obtained through calculation.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioners, and in particular to a method, device, equipment and storage medium for evaluating the comfort state of an air conditioner. Background Art

[0002] In traditional technology, in order to improve the user experience when using air conditioning, the general user controls the various components of the air conditioner so that the indoor environment reaches the user's expected comfort level. However, the current comfort evaluation of a single user when using an air conditioner is easily affected by the scores of the surveyed users and is not very accurate.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a method, device, equipment and storage medium for evaluating the comfort state of an air conditioner, aiming to solve the technical problem in the prior art that the accuracy of the comfort evaluation when a user uses an air conditioner is not high.

[0005] To achieve the above object, the present invention provides a method for evaluating the comfort state of an air conditioner, the method comprising the following steps:

[0006] When the air conditioner is running, obtaining a plurality of air conditioner operation data;

[0007] Calculate the distribution distance between each air conditioner operation data and the user bin data respectively;

[0008] A comfort index is generated according to the distribution distance, and a comfort state of the air conditioner is evaluated according to the comfort index.

[0009] Optionally, before respectively calculating the distribution distance between each air conditioner operation data and the user binned data, the method further includes:

[0010] Get the historical number of adjustments made by the target user within a preset time period;

[0011] The target user is divided into boxes according to the number of historical adjustments to obtain a plurality of user boxes, wherein the user boxes correspondingly store user box data, and the user box data is the user's indoor thermal state data.

[0012] Optionally, before obtaining the number of historical adjustments of the target user within a preset historical duration, the method further includes:

[0013] Get user group information of multiple users;

[0014] Determining information tags of the user group information;

[0015] Grouping each user according to the information tag to obtain multiple user groups;

[0016] A target user group and a target user within the target user group are determined according to preset feature tags.

[0017] Optionally, respectively calculating the distribution distance between each air conditioner operation data and the user binned data includes:

[0018] determining the number of samples of the plurality of air conditioner operation data;

[0019] When the number of samples is less than or equal to a preset threshold, the distribution distance between the operation data of each air conditioner and the user's boxed data is calculated respectively.

[0020] Optionally, the air conditioner comfort state evaluation method further includes:

[0021] When the number of samples is greater than a preset threshold, extracting a preset threshold number of target air conditioner operation data from the plurality of air conditioner operation data;

[0022] The distribution distance between each target air conditioner operation data and the user bin data is calculated respectively.

[0023] Optionally, generating a comfort index according to the distribution distance, and evaluating a comfort state of the air conditioner according to the comfort index includes:

[0024] Determine a minimum value of the distribution distance and a target bin corresponding to the minimum value;

[0025] Obtain the bin number and bin attributes of the target bin;

[0026] Generating a comfort index according to the bin sequence number and the total number of bins of the preset user bins;

[0027] The comfort state of the air conditioner is evaluated according to the comfort index and the box attributes.

[0028] Optionally, the distribution distance includes at least one of a maximum mean difference distance, a relative entropy divergence distance, a domain distribution offset distance and a cosine distance.

[0029] In addition, to achieve the above-mentioned purpose, the present invention also provides a comfort state evaluation device for an air conditioner, the comfort state evaluation device for an air conditioner comprising:

[0030] An acquisition module, used for acquiring a plurality of air conditioner operation data when the air conditioner is running;

[0031] A calculation module, used to calculate the distribution distance between the operation data of each air conditioner and the user's binned data;

[0032] An evaluation module is used to generate a comfort index according to the distribution distance, and evaluate the comfort state of the air conditioner according to the comfort index.

[0033] In addition, to achieve the above-mentioned purpose, the present invention also proposes a comfort state evaluation device for an air conditioner, wherein the comfort state evaluation device for an air conditioner comprises: a memory, a processor, and a comfort state evaluation program for an air conditioner stored on the memory and executable on the processor, wherein the comfort state evaluation program for the air conditioner is configured to implement the steps of the comfort state evaluation method for the air conditioner as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a comfort state evaluation program of an air conditioner is stored. When the comfort state evaluation program of the air conditioner is executed by a processor, the steps of the comfort state evaluation method of the air conditioner described above are implemented.

[0035] The present invention discloses a method for evaluating the comfort state of an air conditioner, the method comprising: acquiring a plurality of air conditioner operation data when the air conditioner is running; respectively calculating the distribution distance between the operation data of each air conditioner and the user's boxed data; generating a comfort index according to the distribution distance, and evaluating the comfort state of the air conditioner according to the comfort index. Compared with the prior art, the present invention collects a plurality of operation data when the air conditioner is running, and respectively calculates the distribution distance between the operation data of each air conditioner and the user's boxed data, and then generates a comfort index according to the distribution distance, thereby improving the anti-interference ability of the comfort evaluation. Finally, the comfort state of the air conditioner is evaluated with the calculated comfort index, thereby solving the technical problem of low accuracy of the comfort evaluation when the user uses the air conditioner in the prior art and improving the accuracy of the comfort evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a structural schematic diagram of a comfort state evaluation device for an air conditioner in a hardware operating environment involved in an embodiment of the present invention;

[0037] Figure 2 A schematic flow chart of a first embodiment of a method for evaluating a comfortable state of an air conditioner according to the present invention;

[0038] Figure 3 A schematic flow chart of a second embodiment of a method for evaluating a comfortable state of an air conditioner according to the present invention;

[0039] Figure 4 A schematic flow chart of a third embodiment of a method for evaluating a comfortable state of an air conditioner according to the present invention;

[0040] Figure 5It is a structural block diagram of the first embodiment of the comfort state evaluation device for an air conditioner of the present invention.

[0041] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0042] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0043] Reference Figure 1 , Figure 1 The figure is a schematic diagram of the structure of a comfort state evaluation device for an air conditioner in a hardware operating environment according to an embodiment of the present invention.

[0044] like Figure 1 As shown, the comfort state evaluation device of the air conditioner may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0045] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the comfort state evaluation device of the air conditioner, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0046] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a comfort state evaluation program of the air conditioner.

[0047] exist Figure 1In the comfort state evaluation device of the air conditioner shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the comfort state evaluation device of the air conditioner of the present invention can be set in the comfort state evaluation device of the air conditioner, and the comfort state evaluation device of the air conditioner calls the comfort state evaluation program of the air conditioner stored in the memory 1005 through the processor 1001, and executes the comfort state evaluation method of the air conditioner provided in the embodiment of the present invention.

[0048] The embodiment of the present invention provides a method for evaluating the comfort state of an air conditioner, referring to Figure 2 , Figure 2 The figure is a flow chart of a first embodiment of a method for evaluating the comfort state of an air conditioner according to the present invention.

[0049] In this embodiment, the method for evaluating the comfort state of the air conditioner comprises the following steps:

[0050] Step S10: When the air conditioner is running, a plurality of air conditioner operation data are obtained.

[0051] It should be noted that the execution subject of the method of this embodiment can be the air conditioner device, which has functions such as data processing, data communication and program running, and can also be other devices with the same or similar functions, and this implementation condition does not limit this. For the convenience of explanation, this implementation is described by taking the controller of the air conditioner as an example.

[0052] It should be understood that in traditional technology, in order to achieve comfort control of the air conditioner, the state of each component of the air conditioner is generally adjusted through the human comfort intelligent control model (Predicted Mean Vote, PMV) to make the indoor environment reach the user's comfort state. However, the calculation dependencies of the existing PMV algorithm during training are difficult to collect, resulting in the air conditioner being unable to meet the actual usage needs of the user when it is adjusted. Among them, the human comfort state index is established based on the thermal comfort balance equation, and its calculation involves air temperature, radiation temperature, air humidity, air flow rate, human metabolism and clothing thermal resistance. Some parameters are difficult to collect through the air conditioner's own perception, and it is impossible to accurately calculate the thermal comfort state.

[0053] And affected by the survey group used in model training, the actual operation process cannot meet the comfort requirements of different groups. For example, when the foreign CBE thermal comfort database is used as the training set, the surveyed group is mainly European and American people. The PMV model based on the CBE database cannot be applied to the thermal comfort evaluation in domestic areas, and there are large differences.

[0054] It should be noted that the air conditioner operating data includes but is not limited to: environmental information, operating condition information and user setting information, wherein the environmental information includes indoor ambient temperature, indoor ambient humidity and outdoor thermal environment information, the operating condition information includes fan speed, throttling element opening and windshield opening, etc., and the user setting information includes user-set temperature and air conditioner operating mode, etc. This embodiment does not make specific restrictions on this.

[0055] In a specific implementation, when the air conditioner is running, the operating data of the air conditioner can be collected at preset periods, and periodic characteristics in the operating data can be extracted: including but not limited to environmental information, operating condition information, and user setting information, etc. The preset period can be 30s or 1min, and can also be set by the user. This embodiment does not impose specific restrictions on this.

[0056] Step S20: Calculate the distribution distance between each air conditioner operation data and the user bin data respectively.

[0057] It can be understood that user data binning refers to dividing user data into several discrete intervals (also called boxes). In this embodiment, the basis for user binning can be determined according to the number of times the user adjusts the air conditioner, and this embodiment does not impose specific restrictions on this.

[0058] Among them, user binning data refers to user group information, including but not limited to: gender, age, region, temperature setting habits, and historical preferences.

[0059] In the specific implementation process, the distribution distance is mainly used as a metric to measure the difference between two data; the distribution distance between each air conditioner operation data and the user box data can be calculated by calculating the maximum mean difference distance (Maximum mean discrepancy, MMD), relative entropy divergence distance (Kolmogorov-Smirnov, KS), domain distribution offset distance (Coral distance) and cosine distance, etc., which are not specifically limited in this embodiment.

[0060] Step S30: generating a comfort index according to the distribution distance, and evaluating the comfort state of the air conditioner according to the comfort index.

[0061] It should be noted that when calculating the comfort index, the distance between different bins of the operating data of each air conditioner may be calculated, and then the target bin with the smallest distance is taken, and the comfort index is determined based on the ratio of the target bin to the number of all bins.

[0062] Further, generating a comfort index according to the distribution distance, and evaluating the comfort state of the air conditioner according to the comfort index, includes:

[0063] Determine a minimum value of the distribution distance and a target bin corresponding to the minimum value;

[0064] Obtain the bin number and bin attributes of the target bin;

[0065] Generating a comfort index according to the bin sequence number and the total number of bins of the preset user bins;

[0066] The comfort state of the air conditioner is evaluated according to the comfort index and the box attributes.

[0067] In a specific implementation, since the user boxes in this embodiment are divided into boxes according to the number of times the user adjusts the air conditioner, if all user data are divided into 20 boxes according to the number of adjustments from small to large, when calculating the comfort index, if the target box number is 5, the comfort index is 5 / 20=0.25, the more comfortable; if all user data are divided into 20 boxes according to the number of adjustments from small to large, when calculating the comfort index, if the target box number is 5, the comfort index is 5 / 20=0.25, the more uncomfortable.

[0068] It is understandable that the bin attributes may be the ratio of the number of adjustments stored in the bin and the sharing rules, etc., and this embodiment does not impose any specific limitation on this.

[0069] This embodiment collects multiple operating data of the air conditioner during operation, and calculates the distribution distance between the operating data of each air conditioner and the user's boxed data, and then generates a comfort index based on the distribution distance to improve the anti-interference ability of the comfort evaluation. Finally, the comfort state of the air conditioner is evaluated based on the calculated comfort index. The technical problem of low accuracy of comfort evaluation when users use air conditioners in the prior art is solved, and the accuracy of comfort evaluation is improved.

[0070] refer to Figure 3 , Figure 3 It is a flow chart of a second embodiment of a method for evaluating the comfort state of an air conditioner according to the present invention.

[0071] Based on the first embodiment above, in this embodiment, before step S20, the following steps are further included:

[0072] Step S110: Obtain the historical adjustment times of the target user within a preset time period.

[0073] It should be noted that the target user refers to a user with a specific feature tag, for example: Shanghai + male + age range 20-30 + user with set temperature history preference, to obtain the historical adjustment times of males living in Shanghai and aged 20-30 years old. This embodiment does not impose specific restrictions on this.

[0074] The preset time can be set to the past week or month. Considering that the use of the air conditioner is affected by the season, the historical adjustment times in this embodiment can also be the historical adjustment times in the same season in historical years. This embodiment does not impose specific restrictions on this.

[0075] Furthermore, before obtaining the target user's historical adjustment times within a preset historical time period, the method further includes:

[0076] Get user group information of multiple users;

[0077] Determining information tags of the user group information;

[0078] Grouping each user according to the information tag to obtain multiple user groups;

[0079] A target user group and a target user within the target user group are determined according to preset feature tags.

[0080] It is understandable that user group information includes but is not limited to gender, age, region, and temperature setting temperature historical preference information, etc., wherein the region information can be determined by machine code pairing (SN pairing) or wifi network location or IP address, etc., and the gender information refers to the gender (male or female) of the users participating in the user survey; the setting temperature historical preference information can be obtained by obtaining the distribution of all setting temperatures, such as the users whose historical setting temperature preference (such as historical mean) falls in the lower 30% (percentile), their label is cold; the users who fall in 30%-70% are labeled as neutral; the users who fall in >70% are labeled as hot.

[0081] Step S120: binning the target user according to the number of historical adjustments to obtain a plurality of user bins, wherein the user bins store corresponding user bin data, and the user bin data is the user's indoor thermal state data.

[0082] It should be noted that when the target users are divided into boxes according to the number of historical adjustments, all the target users can be divided into a preset number of users for sharing according to the number of historical adjustments of each user from small to large. The user boxes correspondingly store user box data and information such as the number of air conditioners. The indoor thermal status data includes but is not limited to indoor temperature T1, indoor humidity H, and windshield opening Wi, among which the number of user boxes can be set by oneself, and this embodiment does not impose specific restrictions on this.

[0083] In a specific implementation, if the bins are divided from small to large according to the number of adjustments, then bin group 1 represents the users with the least number of adjustments stored. For example, if the entire user group is divided into 20 bins, bin group 1 stores users with a percentile of 0-5% of the number of adjustments, bin group 2 stores users with a percentile of 5-10% of the number of adjustments, and so on, until all bins contain user sharing data.

[0084] This embodiment divides users into bins based on the number of historical adjustments made by them within a preset time period, and quantifies the users' sense of comfort by the number of adjustments, so that a more accurate comfort evaluation can be achieved in the subsequent calculation of the distribution distance and the comfort index.

[0085] refer to Figure 4 , Figure 4 It is a flow chart of a third embodiment of a method for evaluating the comfort state of an air conditioner according to the present invention.

[0086] Based on the above second embodiment, in this embodiment, step S20 includes:

[0087] Step S201: Determine the number of samples of the plurality of air conditioner operation data.

[0088] It should be noted that in order to obtain a more accurate comfort index, this embodiment needs to collect a certain amount of air conditioner operation data, and then accurately calculate the distribution distance between the air conditioner operation data set and the user box data set without causing overfitting due to the large difference in data volume. At this time, if the sample data of the air conditioner is sufficient, the distribution distance between each air conditioner operation data and the user box data can be directly calculated.

[0089] Step S201: When the number of samples is less than or equal to a preset threshold, respectively calculating the distribution distance between each air conditioner operation data and the user binned data.

[0090] In this embodiment, the preset threshold can be set to 20, that is, when the number of air conditioner operation data collected most recently is less than or equal to 20, due to the limited amount of data, the distribution distance between each air conditioner operation data and the user box data can only be calculated at the expense of a certain accuracy, thereby calculating the comfort index.

[0091] Further, when the number of samples is greater than a preset threshold, extracting a preset threshold number of target air conditioner operation data from the plurality of air conditioner operation data;

[0092] The distribution distance between each target air conditioner operation data and the user bin data is calculated respectively.

[0093] In a specific implementation, if the number of recently collected air conditioner operation data is greater than 20, in order to improve the accuracy of the comfort evaluation, this embodiment can extract 20 target air conditioner operation data from the collected multiple air conditioner operation data by uniform sampling for calculating the distribution distance.

[0094] In addition, an embodiment of the present invention further proposes a storage medium on which a comfort state evaluation program for an air conditioner is stored. When the comfort state evaluation program for an air conditioner is executed by a processor, the steps of the comfort state evaluation method for an air conditioner as described above are implemented.

[0095] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0096] Reference Figure 5 , Figure 5 It is a structural block diagram of the first embodiment of the comfort state evaluation device for an air conditioner of the present invention.

[0097] like Figure 5 As shown, the comfort state evaluation device for an air conditioner provided in an embodiment of the present invention comprises:

[0098] The acquisition module 10 is used to acquire a plurality of air conditioner operation data when the air conditioner is running.

[0099] The calculation module 20 is used to respectively calculate the distribution distance between each air conditioner operation data and the user's box data.

[0100] The evaluation module 30 is used to generate a comfort index according to the distribution distance, and evaluate the comfort state of the air conditioner according to the comfort index.

[0101] In one embodiment, the calculation module 20 is also used to obtain the historical adjustment times of the target user within a preset time period; the target user is divided into boxes according to the historical adjustment times to obtain multiple user boxes, and the user boxes correspond to the storage of user box data, and the user box data is the user's indoor thermal status data.

[0102] In one embodiment, the calculation module 20 is further used to obtain user group information of multiple users; determine information tags of the user group information; group each user according to the information tags to obtain multiple user groups; and determine a target user group and a target user within the target user group according to a preset feature tag.

[0103] In one embodiment, the calculation module 20 is further used to determine the sample number of the plurality of air conditioner operation data; when the sample number is less than or equal to a preset threshold, the distribution distance between each air conditioner operation data and the user box data is calculated respectively.

[0104] In one embodiment, the calculation module 20 is also used to extract a preset threshold number of target air conditioner operation data from the multiple air conditioner operation data when the sample quantity is greater than the preset threshold; and respectively calculate the distribution distance between each target air conditioner operation data and the user box data.

[0105] In one embodiment, the calculation module 20 is also used to determine the minimum value of the distribution distance and the target bin corresponding to the minimum value; obtain the bin number and bin attributes of the target bin; generate a comfort index based on the bin number and the total number of bins of the preset user bin; and evaluate the comfort state of the air conditioner based on the comfort index and the bin attributes.

[0106] In one embodiment, the calculation module 20 is further used for the distribution distance to include at least one of a maximum mean difference distance, a relative entropy divergence distance, a domain distribution offset distance and a cosine distance.

[0107] This embodiment collects multiple operating data of the air conditioner during operation, and calculates the distribution distance between the operating data of each air conditioner and the user's boxed data, and then generates a comfort index based on the distribution distance to improve the anti-interference ability of the comfort evaluation. Finally, the comfort state of the air conditioner is evaluated based on the calculated comfort index. The technical problem of low accuracy of comfort evaluation when users use air conditioners in the prior art is solved, and the accuracy of comfort evaluation is improved.

[0108] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are displayed in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and it can be performed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0109] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0110] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0111] In addition, for technical details that are not described in detail in this embodiment, reference can be made to the comfort state evaluation method for an air conditioner provided in any embodiment of the present invention, and will not be repeated here.

[0112] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0113] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0114] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0115] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for evaluating the comfort state of an air conditioner, characterized in that: The comfort state evaluation method of the air conditioner comprises: When the air conditioner is running, obtaining a plurality of air conditioner operation data; Calculate the distribution distance between each air conditioner operation data and the user bin data respectively; A comfort index is generated according to the distribution distance, and a comfort state of the air conditioner is evaluated according to the comfort index.

2. The method for evaluating the comfort state of an air conditioner according to claim 1, characterized in that: Before respectively calculating the distribution distance between each air conditioner operation data and the user binned data, the method further includes: Get the historical number of adjustments made by the target user within a preset time period; The target user is divided into boxes according to the number of historical adjustments to obtain a plurality of user boxes, wherein the user boxes correspondingly store user box data, and the user box data is the user's indoor thermal state data.

3. The method for evaluating the comfort state of an air conditioner according to claim 2, characterized in that: Before obtaining the target user's historical adjustment times within a preset historical time period, the method further includes: Get user group information of multiple users; Determining information tags of the user group information; Grouping each user according to the information tag to obtain multiple user groups; A target user group and a target user within the target user group are determined according to preset feature tags.

4. The method for evaluating the comfort state of an air conditioner according to claim 1, wherein: The respectively calculating the distribution distance between each air conditioner operation data and the user binned data includes: determining the number of samples of the plurality of air conditioner operation data; When the number of samples is less than or equal to a preset threshold, the distribution distance between the operation data of each air conditioner and the user's boxed data is calculated respectively.

5. The method for evaluating the comfort state of an air conditioner according to claim 4, characterized in that: The method for evaluating the comfort state of the air conditioner further comprises: When the number of samples is greater than a preset threshold, extracting a preset threshold number of target air conditioner operation data from the plurality of air conditioner operation data; The distribution distance between each target air conditioner operation data and the user bin data is calculated respectively.

6. The method for evaluating the comfort state of an air conditioner according to any one of claims 1 to 5, characterized in that: Generating a comfort index according to the distribution distance, and evaluating the comfort state of the air conditioner according to the comfort index, comprises: Determine a minimum value of the distribution distance and a target bin corresponding to the minimum value; Obtain the bin number and bin attributes of the target bin; Generating a comfort index according to the bin sequence number and the total number of bins of the preset user bins; The comfort state of the air conditioner is evaluated according to the comfort index and the box attributes.

7. The method for evaluating the comfort state of an air conditioner according to any one of claims 1 to 5, characterized in that: The distribution distance includes at least one of a maximum mean difference distance, a relative entropy divergence distance, a domain distribution offset distance and a cosine distance.

8. A comfort state evaluation device for an air conditioner, characterized in that: The comfort state evaluation device of the air conditioner comprises: An acquisition module, used for acquiring a plurality of air conditioner operation data when the air conditioner is running; A calculation module, used to calculate the distribution distance between the operation data of each air conditioner and the user's binned data; An evaluation module is used to generate a comfort index according to the distribution distance, and evaluate the comfort state of the air conditioner according to the comfort index.

9. A comfort state evaluation device for an air conditioner, characterized in that: The comfort state evaluation device of the air conditioner includes: a memory, a processor, and a comfort state evaluation program of the air conditioner stored in the memory and executable on the processor, wherein the comfort state evaluation program of the air conditioner is configured to implement the comfort state evaluation method of the air conditioner as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a comfort state evaluation program for an air conditioner, and when the comfort state evaluation program for an air conditioner is executed by a processor, the comfort state evaluation method for an air conditioner as described in any one of claims 1 to 7 is implemented.

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