User evaluation method and device based on data analysis, equipment and storage medium

Abstract

The invention belongs to the technical field of user evaluation, and discloses a user evaluation method and device based on data analysis, equipment and a storage medium. The method comprises the following steps: acquiring gas supply and output data of a plurality of to-be-evaluated users; dividing the gas supply and output data based on preset index classification to obtain input index data and output index data; classifying the plurality of to-be-evaluated users according to the input index data and the output index data, and screening out a plurality of types of to-be-evaluated users based on a classification result; based on the input index data and the output index data, constructing an evaluation index system of the plurality of types of to-be-evaluated users; and determining the evaluation level of each user corresponding to the plurality of types of to-be-evaluated users based on the evaluation index system. By means of the mode, the users are screened and the corresponding evaluation grades are determined by means of the index data through data analysis, so that the users are evaluated, and objectivity and comprehensiveness of evaluation can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of user evaluation, and in particular to a user evaluation method, device, equipment and storage medium based on data analysis. Background Art

[0002] In order to make full use of gas supply capacity, alleviate peak-shaving pressure, and reasonably meet the market demand of downstream users, it is of great significance to make adjustments to downstream users.

[0003] Currently, adjustments to downstream users are made through user evaluation, but the current evaluation method is mainly manual, and there are problems with the evaluation being not objective and comprehensive enough.

[0004] 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

[0005] The main purpose of the present invention is to provide a user evaluation method, device, equipment and storage medium based on data analysis, aiming to solve the technical problem that the current evaluation method is mainly based on manual methods, and the evaluation is not objective and comprehensive enough.

[0006] To achieve the above object, the present invention provides a user evaluation method based on data analysis, the method comprising the following steps:

[0007] Obtain gas supply and output data of several users to be evaluated;

[0008] Dividing the gas supply and output data based on preset index classification to obtain input index data and output index data;

[0009] Classifying the plurality of users to be evaluated according to the input indicator data and the output indicator data, and selecting a plurality of users to be evaluated in a first category based on the classification results;

[0010] Constructing an evaluation index system for the plurality of first-class users to be evaluated based on the input index data and the output index data;

[0011] An evaluation level of each user corresponding to the plurality of first-class users to be evaluated is determined based on the evaluation index system.

[0012] In some embodiments, the classifying the plurality of users to be evaluated according to the input indicator data and the output indicator data, and selecting a plurality of users to be evaluated in a first category based on the classification results, includes:

[0013] Determine the efficiency index value of each user to be evaluated according to the input index data and the output index data;

[0014] Compare the efficiency index values ​​of each user to be evaluated with the preset index values;

[0015] A number of users to be evaluated whose efficiency index values ​​are less than a preset index value are screened out as a category of users to be evaluated.

[0016] In some embodiments, determining the efficiency index value of each to-be-evaluated user according to the input index data and the output index data includes:

[0017] Inputting the input index data and the output index data into a decision unit of a preset efficiency evaluation model;

[0018] The efficiency index value is calculated according to the number of decision-making units, the number of input index data, the number of input index data, and the input index data and output index data input to each decision-making unit. The calculation formula of the efficiency index value is: Among them, h j is the jth decision making unit, y sj is the sth output indicator of the jth decision-making unit, x ij is the i-th input index of the j-th decision-making unit, v i and u s are the weights corresponding to the ith input indicator and the sth output indicator respectively, n, m and k are the number of decision-making units, the number of input indicator data and the number of input output indicator data respectively.

[0019] In some embodiments, determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the evaluation index system includes:

[0020] Determine the importance ratio between the various evaluation indicators based on the evaluation indicator system using the nine-scale method;

[0021] Constructing a judgment matrix according to the importance ratios between the evaluation indicators;

[0022] The evaluation level of each user corresponding to the plurality of first-category users to be evaluated is determined based on the judgment matrix.

[0023] In some embodiments, determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the judgment matrix includes:

[0024] Calculate the product of each row of factors in the judgment matrix;

[0025] Calculating a square root based on the product of each row of factors;

[0026] Constructing a weighted feature vector corresponding to the evaluation index of each user based on the square root;

[0027] A corresponding evaluation level is determined according to the weight feature vector.

[0028] In some embodiments, the method further comprises:

[0029] Determining a consistency ratio of the judgment matrix;

[0030] If the consistency ratio is less than a preset ratio, it is determined that the judgment matrix passes the consistency check;

[0031] After the judgment matrix passes the consistency check, the step of determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the judgment matrix is ​​performed.

[0032] In some embodiments, the method further comprises:

[0033] Determine the user type corresponding to each category of users to be evaluated;

[0034] Based on the evaluation level, a number of target users are screened for each user type;

[0035] Increase the gas supply to the target users.

[0036] In addition, to achieve the above-mentioned purpose, the present invention further proposes a user evaluation device based on data analysis, and the user evaluation device based on data analysis comprises:

[0037] An acquisition module is used to obtain gas supply and output data of several users to be evaluated;

[0038] A division module, used to divide the gas supply and output data based on preset index classification to obtain input index data and output index data;

[0039] A screening module, used for classifying the plurality of users to be evaluated according to the input index data and the output index data, and screening out a plurality of users to be evaluated in a first category based on the classification result;

[0040] A construction module, used to construct an evaluation index system for the plurality of first-category users to be evaluated based on the input index data and the output index data;

[0041] An evaluation module is used to determine the evaluation level of each user corresponding to the plurality of first-class users to be evaluated based on the evaluation index system.

[0042] In addition, to achieve the above-mentioned purpose, the present invention also proposes a user evaluation device based on data analysis, and the user evaluation device based on data analysis includes: a memory, a processor, and a user evaluation program based on data analysis stored in the memory and executable on the processor, and the user evaluation program based on data analysis is configured to implement the steps of the user evaluation method based on data analysis as described above.

[0043] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a user evaluation program based on data analysis is stored. When the user evaluation program based on data analysis is executed by a processor, the steps of the user evaluation method based on data analysis as described above are implemented.

[0044] In the present invention, the gas supply and output data of several users to be evaluated are obtained; the gas supply and output data are divided based on the preset index classification to obtain input index data and output index data; the several users to be evaluated are classified according to the input index data and the output index data, and several first-class users to be evaluated are screened out based on the classification results; an evaluation index system for the several first-class users to be evaluated is constructed based on the input index data and the output index data; and the evaluation level of each user corresponding to the several first-class users to be evaluated is determined based on the evaluation index system. In the above manner, data analysis is used to screen users with the help of index data and determine the corresponding evaluation level to achieve user evaluation, which can ensure the objectivity and comprehensiveness of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a flow chart of a first embodiment of a user evaluation method based on data analysis of the present invention;

[0046] Figure 2 This is a structural block diagram of the first embodiment of the user evaluation device based on data analysis of the present invention.

[0047] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0048] 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.

[0049] The embodiment of the present invention provides a user evaluation method based on data analysis, referring to Figure 1 , Figure 1 The figure is a flow chart of a first embodiment of a user evaluation method based on data analysis according to the present invention.

[0050] In this embodiment, the user evaluation method based on data analysis includes the following steps:

[0051] Step S10: Obtain gas supply and output data of several users to be evaluated.

[0052] In this embodiment, the executor of this embodiment is a user evaluation device based on data analysis, wherein the user evaluation device based on data analysis has functions such as data processing, data communication and program running. The user evaluation device based on data analysis can be a computer terminal device or other network device, and of course it can also be other devices with similar functions, and this embodiment does not limit this.

[0053] It should be noted that currently the adjustment of downstream users is achieved through user evaluation, but the current evaluation method is mainly manual, and there are problems such as lack of objectivity and comprehensiveness.

[0054] In order to solve the above technical problems, in this embodiment, the gas supply and output data of several users to be evaluated are obtained; the gas supply and output data are divided based on the preset index classification to obtain input index data and output index data; the several users to be evaluated are classified according to the input index data and the output index data, and several first-class users to be evaluated are screened out based on the classification results; an evaluation index system for the several first-class users to be evaluated is constructed based on the input index data and the output index data; and the evaluation level of each user corresponding to the several first-class users to be evaluated is determined based on the evaluation index system. In the above manner, data analysis is used to screen users with the help of index data and determine the corresponding evaluation level to achieve user evaluation, which can ensure the objectivity and comprehensiveness of the evaluation. Specifically, it can be achieved in the following manner.

[0055] In a specific implementation, in this embodiment, it is necessary to first obtain gas supply and output data of several users to be evaluated, where the gas supply and output data refers to the gas supply volume to the user and the output of the user based on the gas supply volume.

[0056] Step S20: Divide the gas supply and output data based on preset index classification to obtain input index data and output index data.

[0057] After obtaining the above-mentioned gas supply and output data, the gas supply and output data can be divided into input indicators and output indicator data. In this embodiment, the preset indicator classification includes input indicators and output indicators. The input indicators include commodity gas input, cost, freight, and sales personnel input. The output indicators include peak-shaving contribution, recovered gas fees, and sales price. The division of input indicator data and output indicator data can be achieved through the above-mentioned preset indicator classification.

[0058] Step S30: classifying the plurality of users to be evaluated according to the input indicator data and the output indicator data, and selecting a plurality of first-class users to be evaluated based on the classification results.

[0059] In a specific implementation, in this embodiment, users are first classified according to input index data and output index data, so as to screen out a number of users to be evaluated in a certain category. The specific screening process is to determine the efficiency index value of each user to be evaluated according to the input index data and the output index data; compare the efficiency index value of each user to be evaluated with the preset index value; and screen out a number of users to be evaluated whose efficiency index values ​​are less than the preset index value as a category of users to be evaluated.

[0060] It should be noted that the preset index value can be set to 1. If the efficiency index value is 1, it means that the gas consumption is large and the cost is low, indicating that the input and output of these users match, and they are the most valuable users. This type of user belongs to the second type of users to be evaluated, and such high value does not need to be evaluated in this embodiment. The other part of users is the first type of users to be evaluated. The efficiency index values ​​of these first type of users to be evaluated are less than the preset index value, indicating that the input-output efficiency of this type of users is relatively poor.

[0061] Furthermore, the calculation process of the efficiency index value of each user to be evaluated in this embodiment is to input the input index data and the output index data into the decision unit of the preset efficiency evaluation model;

[0062] The efficiency index value is calculated according to the number of decision-making units, the number of inputs of the input index data, the number of inputs of the output index data, and the input index data and output index data input to each decision-making unit. The calculation formula of the efficiency index value is:

[0063]

[0064] Among them, h j is the jth decision making unit, y sj is the sth output indicator of the jth decision-making unit, x ij is the i-th input index of the j-th decision-making unit, v i and u s are the weights corresponding to the ith input indicator and the sth output indicator respectively, n, m and k are the number of decision-making units, the number of input indicator data and the number of input output indicator data respectively.

[0065] Step S40: constructing an evaluation index system for the plurality of first-category users to be evaluated based on the input index data and the output index data.

[0066] The evaluation index system in this embodiment includes two layers. For example, the first layer of the evaluation index system is the user's gas usage level. The second layer is in a progressive relationship with the first layer. The second layer can be the user's gas usage ratio and gas price ratio. The first layer of the evaluation index system can also include gas usage characteristics and development potential, etc. Specific evaluation items can be set according to actual needs, and this is not limited in this embodiment.

[0067] Step S50: determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the evaluation index system.

[0068] In a specific implementation, the calculation process of the evaluation level is to use the nine-scale method to determine the importance ratio between each evaluation indicator based on the evaluation indicator system; construct a judgment matrix according to the importance ratio between each evaluation indicator; and determine the evaluation level of each user corresponding to the several types of users to be evaluated based on the judgment matrix.

[0069] It should be noted that, assuming that the importance ratio between the evaluation indicators is r ij , where i and j represent evaluation index i and evaluation index j respectively, r ij can be greater than 0 or 1. The constructed judgment matrix is ​​expressed as T = (r ij ).

[0070] Among them, determining the evaluation level of each user corresponding to the several types of users to be evaluated based on the judgment matrix further includes calculating the product of factors in each row of the judgment matrix; calculating the square root based on the product of the factors in each row; constructing a weighted feature vector corresponding to the evaluation index of each user based on the square root; and determining the corresponding evaluation level according to the weighted feature vector.

[0071] It should be noted that the product of the factors in each row of the judgment matrix Square root of n The final weighted feature vector is ω=[ω 1 ,ω 2 ,...,ω n ] T .

[0072] In some embodiments, before executing the step of determining the evaluation level of each user corresponding to the several types of users to be evaluated based on the judgment matrix, it is necessary to first obtain the consistency ratio of the judgment matrix in this embodiment. If the consistency ratio is less than the preset ratio, it is determined that the judgment matrix passes the consistency check. The above operation is performed again when the judgment matrix passes the consistency check.

[0073] It should be noted that the calculation formula of the consistency ratio of the judgment matrix in this embodiment is CR=CI / RI, where CI=(λ max -n) / (n-1), λ max is the maximum eigenvalue of the judgment matrix, n is the number of pairwise comparison factors, RI is a random consistency index, RI is a pre-calculated value used to measure the consistency level of the randomly constructed judgment matrix, and the value of RI can be determined based on the order of the judgment matrix. For example, when the order is 3, the corresponding RI is 0.58, and when the order is 5, the corresponding RI is 1.12. The preset ratio can be set to 0.1. If CI is less than 0.1, it is determined that the judgment matrix passes the consistency check. The preset ratio can also be adjusted accordingly according to actual needs, which is not limited in this embodiment.

[0074] Furthermore, after obtaining the evaluation level of each user, this embodiment classifies several types of users to be evaluated, such as urban gas users and industrial gas users, etc. Each type has users with higher evaluation levels, and several users with higher evaluation levels can be screened out as target users. For example, the top 10 users in the rating level can be used as target users. The specific number of screens can also be set according to actual conditions, and this is not limited in this embodiment. After determining the target users, the gas supply can also be increased to a certain extent for these users, while reducing the gas supply for other users.

[0075] In this embodiment, the gas supply and output data of several users to be evaluated are obtained; the gas supply and output data are divided based on the preset index classification to obtain input index data and output index data; the several users to be evaluated are classified according to the input index data and the output index data, and several first-class users to be evaluated are screened out based on the classification results; an evaluation index system for the several first-class users to be evaluated is constructed based on the input index data and the output index data; and the evaluation level of each user corresponding to the several first-class users to be evaluated is determined based on the evaluation index system. In the above manner, data analysis is used to screen users with the help of index data and determine the corresponding evaluation level to achieve user evaluation, which can ensure the objectivity and comprehensiveness of the evaluation.

[0076] In addition, an embodiment of the present invention further proposes a storage medium, on which a user evaluation program based on data analysis is stored. When the user evaluation program based on data analysis is executed by a processor, the steps of the user evaluation method based on data analysis as described above are implemented.

[0077] Reference Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the user evaluation device based on data analysis of the present invention.

[0078] like Figure 2 As shown, the user evaluation device based on data analysis proposed in the embodiment of the present invention includes:

[0079] An acquisition module 10 is used to acquire gas supply and output data of a number of users to be evaluated;

[0080] A division module 20, for dividing the gas supply and output data based on preset index classification to obtain input index data and output index data;

[0081] A screening module 30, for classifying the plurality of users to be evaluated according to the input index data and the output index data, and screening out a plurality of first-class users to be evaluated based on the classification results;

[0082] A construction module 40 is used to construct an evaluation index system for the plurality of first-category users to be evaluated based on the input index data and the output index data;

[0083] The evaluation module 50 is used to determine the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the evaluation index system.

[0084] In this embodiment, the gas supply and output data of several users to be evaluated are obtained; the gas supply and output data are divided based on the preset index classification to obtain input index data and output index data; the several users to be evaluated are classified according to the input index data and the output index data, and several first-class users to be evaluated are screened out based on the classification results; an evaluation index system for the several first-class users to be evaluated is constructed based on the input index data and the output index data; and the evaluation level of each user corresponding to the several first-class users to be evaluated is determined based on the evaluation index system. In the above manner, data analysis is used to screen users with the help of index data and determine the corresponding evaluation level to achieve user evaluation, which can ensure the objectivity and comprehensiveness of the evaluation.

[0085] In some embodiments, the screening module 30 is used to determine the efficiency index value of each user to be evaluated according to the input index data and the output index data;

[0086] Compare the efficiency index values ​​of each user to be evaluated with the preset index values;

[0087] A number of users to be evaluated whose efficiency index values ​​are less than a preset index value are screened out as a category of users to be evaluated.

[0088] In some embodiments, the screening module 30 is used to input the input index data and the output index data into a decision unit of a preset efficiency evaluation model;

[0089] The efficiency index value is calculated according to the number of decision-making units, the number of input index data, the number of input index data, and the input index data and output index data input to each decision-making unit. The calculation formula of the efficiency index value is: Among them, h j is the jth decision making unit, y sj is the sth output indicator of the jth decision-making unit, x ij is the i-th input index of the j-th decision-making unit, v i and u s are the weights corresponding to the ith input indicator and the sth output indicator respectively, n, m and k are the number of decision-making units, the number of input indicator data and the number of input output indicator data respectively.

[0090] In some embodiments, the evaluation module 50 is used to determine the importance ratio between the various evaluation indicators based on the evaluation indicator system using the nine-scale method;

[0091] Constructing a judgment matrix according to the importance ratios between the evaluation indicators;

[0092] The evaluation level of each user corresponding to the plurality of first-category users to be evaluated is determined based on the judgment matrix.

[0093] In some embodiments, the evaluation module 50 is used to calculate the product of the factors in each row of the judgment matrix;

[0094] Calculating a square root based on the product of each row of factors;

[0095] Constructing a weighted feature vector corresponding to the evaluation index of each user based on the square root;

[0096] A corresponding evaluation level is determined according to the weight feature vector.

[0097] In some embodiments, the evaluation module 50 is used to determine the consistency ratio of the judgment matrix;

[0098] If the consistency ratio is less than a preset ratio, it is determined that the judgment matrix passes the consistency check;

[0099] After the judgment matrix passes the consistency check, the step of determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the judgment matrix is ​​performed.

[0100] In some embodiments, the user evaluation device based on data analysis further includes an adjustment module;

[0101] The adjustment module is used to determine the user type corresponding to each category of users to be evaluated;

[0102] Based on the evaluation level, a number of target users are screened for each user type;

[0103] Increase the gas supply to the target users.

[0104] An embodiment of the present application also provides a user evaluation device based on data analysis, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus, and the memory is used to store a user evaluation program based on data analysis; the processor is used to implement the above-mentioned user evaluation method based on data analysis when executing the program stored in the memory.

[0105] The communication bus mentioned in the above-mentioned user evaluation device based on data analysis can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0106] The communication interface is used for communication between the above-mentioned user evaluation device based on data analysis and other devices.

[0107] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0108] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components.

[0109] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

[0110] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device 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 device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0111] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0112] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0113] 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.

[0114] 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.

[0115] In addition, for technical details not fully described in this embodiment, reference may be made to the user evaluation method based on data analysis provided in any embodiment of the present invention, and will not be repeated here.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] It is understandable that the system provided by the embodiment of the present invention corresponds to the method provided by the embodiment of the present invention, and the explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts in the above method.

Claims

1. A user evaluation method based on data analysis, characterized in that: The user evaluation method based on data analysis includes: Obtain gas supply and output data of several users to be evaluated; Dividing the gas supply and output data based on preset index classification to obtain input index data and output index data; Classifying the plurality of users to be evaluated according to the input indicator data and the output indicator data, and selecting a plurality of users to be evaluated in a first category based on the classification results; Constructing an evaluation index system for the plurality of first-class users to be evaluated based on the input index data and the output index data; An evaluation level of each user corresponding to the plurality of first-class users to be evaluated is determined based on the evaluation index system.

2. The user evaluation method based on data analysis according to claim 1, characterized in that: The step of classifying the plurality of users to be evaluated according to the input indicator data and the output indicator data, and selecting a plurality of users to be evaluated in a first category based on the classification results, includes: Determine the efficiency index value of each user to be evaluated according to the input index data and the output index data; Compare the efficiency index values ​​of each user to be evaluated with the preset index values; A number of users to be evaluated whose efficiency index values ​​are less than a preset index value are screened out as a category of users to be evaluated.

3. The user evaluation method based on data analysis according to claim 2, characterized in that: The step of determining the efficiency index value of each user to be evaluated according to the input index data and the output index data includes: Inputting the input index data and the output index data into a decision unit of a preset efficiency evaluation model; The efficiency index value is calculated according to the number of decision-making units, the number of input index data, the number of input index data, and the input index data and output index data input to each decision-making unit. The calculation formula of the efficiency index value is: Among them, h j is the jth decision making unit, y sj is the sth output indicator of the jth decision-making unit, x ij is the i-th input index of the j-th decision-making unit, v i and u s are the weights corresponding to the ith input indicator and the sth output indicator respectively, n, m and k are the number of decision-making units, the number of input indicator data and the number of input output indicator data respectively.

4. The user evaluation method based on data analysis according to claim 1, characterized in that: Determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the evaluation index system includes: Determine the importance ratio between the various evaluation indicators based on the evaluation indicator system using the nine-scale method; Constructing a judgment matrix according to the importance ratios between the evaluation indicators; The evaluation level of each user corresponding to the plurality of first-category users to be evaluated is determined based on the judgment matrix.

5. The user evaluation method based on data analysis according to claim 4, characterized in that: The step of determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the judgment matrix includes: Calculate the product of each row of factors in the judgment matrix; Calculating a square root based on the product of each row of factors; Constructing a weighted feature vector corresponding to the evaluation index of each user based on the square root; A corresponding evaluation level is determined according to the weight feature vector.

6. The user evaluation method based on data analysis according to claim 4, characterized in that: The method further comprises: Determining a consistency ratio of the judgment matrix; If the consistency ratio is less than a preset ratio, it is determined that the judgment matrix passes the consistency check; After the judgment matrix passes the consistency check, the step of determining the evaluation level of each user corresponding to the plurality of first-category users to be evaluated based on the judgment matrix is ​​performed.

7. The user evaluation method based on data analysis according to any one of claims 1 to 6, characterized in that: The method further comprises: Determine the user type corresponding to each category of users to be evaluated; Based on the evaluation level, a number of target users are screened for each user type; Increase the gas supply to the target users.

8. A user evaluation device based on data analysis, characterized in that: The user evaluation device based on data analysis comprises: An acquisition module is used to obtain gas supply and output data of several users to be evaluated; A division module, used to divide the gas supply and output data based on preset index classification to obtain input index data and output index data; A screening module, used for classifying the plurality of users to be evaluated according to the input index data and the output index data, and screening out a plurality of users to be evaluated in a first category based on the classification result; A construction module, used to construct an evaluation index system for the plurality of first-category users to be evaluated based on the input index data and the output index data; An evaluation module is used to determine the evaluation level of each user corresponding to the plurality of first-class users to be evaluated based on the evaluation index system.

9. A user evaluation device based on data analysis, characterized in that: The user evaluation device based on data analysis comprises: a memory, a processor and a user evaluation program based on data analysis stored in the memory and executable on the processor, wherein the user evaluation program based on data analysis is configured to implement the steps of the user evaluation method based on data analysis as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a user evaluation program based on data analysis, and when the user evaluation program based on data analysis is executed by the processor, the steps of the user evaluation method based on data analysis as described in any one of claims 1 to 7 are implemented.

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