Method, device, equipment and readable medium for evaluating the strength of industrial chain

Abstract

The embodiment of the present application provides an evaluation method, device, equipment and readable medium for the strength of an industrial chain. Among them, the method includes: according to multiple evaluation indicators, the enterprise indicator data of enterprises within the evaluation area within the historical time period is processed to obtain multiple evaluation indicator data of multiple enterprises of the industrial node; according to the multiple evaluation indicator data of multiple enterprises of the industrial node, the threshold of the multiple evaluation indicators of the industrial node is determined, and according to the threshold, the score of the multiple evaluation indicators of the industrial node of the industrial chain is determined; according to the multiple evaluation indicator data of multiple enterprises of the industrial node, the weight of the multiple evaluation indicators of the industrial node is determined, and according to the weight and score, the strength score of the industrial node is determined; according to the strength score of the industrial node, the strength evaluation result of the industrial node is determined. This scheme can effectively evaluate the strength of the industrial nodes of the industrial chain to reflect the strength of the industrial nodes of the industrial chain.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, and in particular, to a method, device, electronic device and computer-readable medium for evaluating the strength of an industrial chain. Background Art

[0002] At present, although my country's strategic emerging industries are developing rapidly, there are still some bottlenecks and chain-breaking links. Traditional industries such as energy, electricity, petroleum, petrochemicals, steel, and nonferrous metals are facing industrial transformation and upgrading to adapt to the ever-changing domestic and international economic forms. In some key areas, core technologies have not yet reached full autonomy and control, and have not yet fully reached the height required for the transformation of new and old kinetic energy and the upgrading of industrial structure. To support the development of related industries, the government should play a leading role and provide necessary policy support. Due to the lack of in-depth understanding of the industrial development situation, the construction of relevant regulatory models and legal and regulatory systems still lags behind the actual situation. The evaluation of the strength of the industrial chain helps to fully and intuitively understand the development status of each industrial node in a certain industrial chain, and continuously improve the level of regional industrial development around building, extending, supplementing, and strengthening the chain, and promote balanced industrial development. In addition, in the work of industrial chain investment promotion, relevant institutions and personnel need to have a good understanding of the development of the local industrial chain and each industrial node in the industrial chain, so as to better formulate investment promotion policies and industrial development plans. However, there is currently a lack of evaluation methods for the strength of the industrial chain in China.

[0003] It can be seen from this that how to effectively evaluate the strength of the industrial nodes of the industrial chain to reflect the strength of the industrial nodes of the industrial chain is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of this application is to propose an evaluation method, device, electronic device and computer-readable medium for the strength of an industrial chain, so as to solve the technical problem existing in the prior art of how to effectively evaluate the strength of the industrial nodes of the industrial chain to reflect the strength of the industrial nodes of the industrial chain.

[0005] According to the first aspect of the embodiment of the present application, a method for evaluating the strength of an industrial chain is provided. The method includes: processing the first enterprise index data of enterprises within the evaluation area in the data warehouse within the historical time period according to multiple evaluation indicators for evaluating the strength of an industrial node of an industrial chain, so as to obtain multiple evaluation index data of multiple enterprises of the industrial node of the industrial chain; determining the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation index data of the multiple enterprises of the industrial node of the industrial chain, and determining the scores of the multiple evaluation indicators of the industrial node of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain; determining the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation index data of the multiple enterprises of the industrial node of the industrial chain, and determining the strength score of the industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain; determining the strength evaluation result of the industrial node of the industrial chain according to the strength score of the industrial node of the industrial chain.

[0006] According to the second aspect of the embodiment of the present application, a device for evaluating the strength of an industrial chain is provided. The device includes: a processing module, which is used to process the first enterprise index data of enterprises within the evaluation area in the data warehouse within the historical time period according to multiple evaluation indicators for evaluating the strength of the industrial node of the industrial chain, so as to obtain multiple evaluation index data of multiple enterprises of the industrial node of the industrial chain; a first determination module, which is used to determine the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation index data of the multiple enterprises of the industrial node of the industrial chain, and determine the scores of the multiple evaluation indicators of the industrial node of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain; a second determination module, which is used to determine the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation index data of the multiple enterprises of the industrial node of the industrial chain, and determine the strength score of the industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain; a third determination module, which is used to determine the strength evaluation result of the industrial node of the industrial chain according to the strength score of the industrial node of the industrial chain.

[0007] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; and a computer-readable medium configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating the strength of the industrial chain as described in the first aspect of the above embodiment.

[0008] According to a fourth aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for evaluating the strength of the industrial chain as described in the first aspect of the above embodiment is implemented.

[0009] Through the evaluation scheme for the strength of the industrial chain provided in the embodiment of the present application, the first enterprise indicator data of the enterprises within the evaluation area in the data warehouse within the historical time period are processed according to multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain to obtain multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, and based on the multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain are determined, and then based on the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain, the scores of the multiple evaluation indicators of the industrial node of the industrial chain are determined, so that the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain can be accurately determined. In addition, based on the multiple evaluation index data of multiple enterprises at the industrial nodes of the industrial chain, the weights of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and based on the weights and scores of the multiple evaluation indexes of the industrial nodes of the industrial chain, the strength score of the industrial node of the industrial chain is determined. Based on the strength score of the industrial node of the industrial chain, the strength evaluation result of the industrial node of the industrial chain can be accurately determined, and then the strength of the industrial nodes of the industrial chain can be effectively evaluated to reflect the strength of the industrial nodes of the industrial chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0011] Figure 1A This is a flowchart of the steps of the method for evaluating the strength of the industrial chain in Example 1 of this application;

[0012] Figure 1B A flowchart of the steps of the method for evaluating the strength of an industrial chain provided in Example 1 of the present application;

[0013] Figure 2 This is a schematic diagram of the structure of the device for evaluating the strength of the industrial chain in the second embodiment of the present application;

[0014] Figure 3 This is a schematic diagram of the structure of the electronic device in the third embodiment of the present application;

[0015] Figure 4 This is the hardware structure of the electronic device in Example 4 of the present application. DETAILED DESCRIPTION

[0016] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only configured to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0017] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0018] Reference Figure 1A , showing a step flow chart of the method for evaluating the strength of the industrial chain in Example 1 of the present application.

[0019] Specifically, the method for evaluating the strength of an industrial chain provided in the embodiment of the present application includes the following steps:

[0020] In step S101, based on multiple evaluation indicators for evaluating the strength of industrial nodes in the industrial chain, the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within a historical time period are processed to obtain multiple evaluation indicator data of multiple enterprises in the industrial nodes of the industrial chain.

[0021] In this embodiment, the industrial chain may be the intelligent connected automobile industrial chain, the industrial nodes may be automobile core parts production (upstream), automobile transmission, automobile body, automobile transmission system, automobile electrical system, planetary gear, clutch, synchronizer, differential, torque converter, hydraulic oil pump, etc., and the evaluation area may be provinces, autonomous regions, municipalities directly under the Central Government and prefecture-level cities. The evaluation index data may be understood as the value of the evaluation index. The multiple evaluation indicators include at least one of the following: industrial chain scale and operating strength, industrial chain R&D and innovation capabilities, industrial chain listed enterprise strength, and industrial chain supply chain robustness. The scale and operating strength of the industrial chain include at least one of the following: the logarithm of the sum of the average output and the average sales volume, the average output, the proportion of output value to regional GDP, and the logarithm of the sum of registered capital; and / or, the R&D and innovation capabilities of the industrial chain include at least one of the following: the average year-on-year change rate of invention patent applications in the past three years, the average year-on-year change rate of patent applications in the past three years, the average year-on-year change rate of the number of patent applicants in the past three years, the average year-on-year change rate of trademark registrations in the past three years, and the average year-on-year change rate of the number of copyrights in the past three years; and / or, the strength of listed companies in the industrial chain includes at least one of the following: the total share capital of listed companies in the industrial chain, the total revenue of listed companies in the industrial chain, the total assets of listed companies in the industrial chain, the total net profit of listed companies in the industrial chain, the total number of employees of listed companies in the industrial chain, the intensity of R&D funding investment of listed companies, the proportion of master and doctoral students in listed companies, the average accounts receivable turnover rate of listed companies in the industrial chain, and the average accounts payable turnover rate of listed companies in the industrial chain; and / or, the robustness of the supply chain of the industrial chain includes at least one of the following: the ratio of the number of upstream and downstream companies in the industrial supply chain, and the ratio of the transaction value of upstream and downstream companies in the industrial supply chain. Overall, the index system is constructed from four parts: the scale and operating strength of the industrial chain, the R&D and innovation capabilities of the industrial chain, the strength of listed companies in the industrial chain, and the robustness of the industrial chain supply chain. The dimensions of the index system are richer and more comprehensive, and it evaluates the strength of the industrial nodes of the industrial chain from all aspects.

[0022] Specifically, the indicator system is shown in Table 1 below:

[0023]

[0024]

[0025] Table 1 Industrial Chain Strength Index System

[0026] Among them, the calculation of registered capital index needs to consider the establishment years of different enterprises, and adopts the weighted summation method. That is, the age of enterprises is divided into different age groups (within 1 year, 1-3 years, 3-5 years, 5-7 years, 7-10 years, and more than 10 years), and different weights are given to enterprises in different age groups, and then the linear weighted sum is taken after logarithm. The average output, output value and sales volume are averaged by the data of the past 2-3 years.

[0027] In some optional embodiments, before processing the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within the historical time period according to multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain, the method also includes: extracting the second enterprise indicator data of enterprises within the evaluation area within the historical time period from multiple enterprise data sources; performing data cleaning on the second enterprise indicator data of enterprises within the evaluation area within the historical time period to obtain the third enterprise indicator data of enterprises within the evaluation area within the historical time period; performing data fusion on the third enterprise indicator data of enterprises within the evaluation area within the historical time period to obtain the first enterprise indicator data of enterprises within the evaluation area within the historical time period; storing the first enterprise indicator data of enterprises within the evaluation area within the historical time period in the data warehouse. Wherein, the second enterprise indicator data can be the original enterprise indicator data, the third enterprise indicator data can be understood as the cleaned enterprise indicator data, and the first enterprise indicator data can be understood as the fused enterprise indicator data. In this way, the first enterprise indicator data of enterprises within the evaluation area within the historical time period can be effectively stored in the data warehouse.

[0028] In a specific example, when cleaning the second enterprise indicator data of the enterprises within the evaluation area within the historical time period, the missing value completion method is used to process the missing values ​​of the second enterprise indicator data of the enterprises within the evaluation area within the historical time period; the clustering algorithm is used to cluster the second enterprise indicator data after the missing value processing to obtain the clustering results of the second enterprise indicator data after the missing value processing; according to the clustering results, the abnormal values ​​in the second enterprise indicator data after the missing value processing are identified, and the abnormal values ​​are eliminated to obtain the third enterprise indicator data of the enterprises within the evaluation area within the historical time period. In this way, the third enterprise indicator data of the enterprises within the evaluation area within the historical time period can be effectively obtained.

[0029] In a specific example, common missing value filling methods include: mean interpolation, same-type mean interpolation, modeling prediction, high-dimensional mapping, multiple interpolation, maximum likelihood estimation, etc. The missing value processing in this model will adopt the same-type mean interpolation method to process missing values. First, the data will be labeled with the industry node, and then the mean of the sample in the industry node will be used to interpolate the missing value. In addition, outliers refer to sample points whose values ​​in the sample are obviously deviated from the rest of the values, so they are also called outliers. Outlier removal is to use clustering algorithms to find these outliers and then remove them.

[0030] In a specific example, when data fusion is performed on the third enterprise indicator data of the enterprises within the evaluation area within the historical time period, the third enterprise indicator data of the enterprises within the evaluation area within the historical time period is statistically summarized through the associated fields of the enterprises to obtain the first enterprise indicator data of the enterprises within the evaluation area within the historical time period.

[0031] In some optional embodiments, when processing the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within a historical time period according to multiple evaluation indicators for evaluating the strength of the industrial node of the industrial chain, the first enterprise indicator data is screened according to the multiple evaluation indicators to obtain the screened first enterprise indicator data; and multiple evaluation indicator data of multiple enterprises of the industrial node of the industrial chain are determined according to the screened first enterprise indicator data. Thus, the multiple evaluation indicator data of multiple enterprises of the industrial node of the industrial chain can be accurately determined through the screened first enterprise indicator data.

[0032] In step S102, based on multiple evaluation index data of multiple enterprises in the industrial nodes of the industrial chain, the thresholds of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and based on the thresholds of the multiple evaluation indexes of the industrial nodes of the industrial chain, the scores of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined.

[0033] In some optional embodiments, when determining the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, the distribution of the evaluation indicator data of the same evaluation indicator of the multiple enterprises of the industrial node of the industrial chain is determined; according to the distribution of the evaluation indicator data of the same evaluation indicator of the multiple enterprises of the industrial node of the industrial chain and the preset distribution ratio, the threshold of the same evaluation indicator of the industrial node of the industrial chain is determined. In this way, the threshold of the same evaluation indicator of the industrial node of the industrial chain can be accurately determined.

[0034] In a specific example, the graphical method refers to plotting the sample data of each evaluation indicator on the graph, and then determining the early warning control line based on the distribution of the points. The general practice is 8%, 12%, 60%, 12% and 8%, which can be adjusted according to the actual situation. The corresponding threshold intervals should be: [92% quantile, 100% quantile], excellent; [80% quantile, 92% quantile), good; [20% quantile, 80% quantile), average; [8% quantile, 20% quantile), poor; [0% quantile, 8% quantile), poor.

[0035] In some optional embodiments, when determining the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain based on the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, the mean and standard deviation of the evaluation indicator data of the same evaluation indicator of the multiple enterprises of the industrial node of the industrial chain are determined; and the threshold of the same evaluation indicator of the industrial node of the industrial chain is determined based on the mean and standard deviation of the evaluation indicator data of the same evaluation indicator of the multiple enterprises of the industrial node of the industrial chain. Thus, the threshold of the same evaluation indicator of the industrial node of the industrial chain can be accurately determined through the mean and standard deviation of the evaluation indicator data of the same evaluation indicator of the multiple enterprises of the industrial node of the industrial chain.

[0036] In a specific example, the mean-standard deviation method means first calculating the sample mean μ and the sample standard deviation σ of each evaluation indicator based on the data of each evaluation indicator, and then calculating μ-2σ, μ-σ, μ, μ+σ and μ+2σ respectively, and using these five values ​​as thresholds.

[0037] In a specific example, the methods for determining the threshold are divided into two categories: one is a more subjective empirical method, such as the growth rate determination method, the graphical method, etc.; the other is a more objective quantitative method based on data calculation, such as the mean-standard deviation method. The determination of the threshold is a process of gradual exploration, adjustment and optimization. The threshold is not constant, but changes with the stage development of the economic operation situation. For historical experience data, special attention should be paid to its usability in the new environment. It is best to use a combination of qualitative analysis and quantitative analysis, and a combination of subjective and objective methods to determine the threshold.

[0038] In some optional embodiments, when determining the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the threshold values ​​of the multiple evaluation indicators of the industrial nodes of the industrial chain, the threshold intervals of the multiple evaluation indicators of the industrial nodes of the industrial chain are determined according to the threshold values ​​of the multiple evaluation indicators of the industrial nodes of the industrial chain; and the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain are determined according to the threshold intervals of the multiple evaluation indicators of the industrial nodes of the industrial chain. Thus, the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain can be accurately determined through the threshold intervals of the multiple evaluation indicators of the industrial nodes of the industrial chain.

[0039] In step S103, the weights of the multiple evaluation indicators of the industrial nodes of the industrial chain are determined based on the multiple evaluation indicator data of the multiple enterprises in the industrial nodes of the industrial chain, and the strength score of the industrial node of the industrial chain is determined based on the weights and scores of the multiple evaluation indicators of the industrial nodes of the industrial chain.

[0040] In some optional embodiments, when determining the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, a stratified random sampling method is used to sample the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain; and the weights of the multiple evaluation indicators of the industrial node of the industrial chain are determined according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling. Thereby, the weights of the multiple evaluation indicators of the industrial node of the industrial chain can be accurately determined through the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling.

[0041] In a specific example, when determining the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling, the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling are dimensionless processed using the power coefficient transformation method; the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after dimensionless processing are weighted; the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain is calculated according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after weight transformation; the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial chain is calculated according to the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain; the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial chain is normalized to obtain the weights of the multiple evaluation indicators of the industrial node of the industrial chain. Thus, the weights of the multiple evaluation indicators of the industrial node of the industrial chain can be accurately obtained through the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain.

[0042] In a specific example, each industrial chain first uses stratified random sampling to obtain data samples, and then builds an entropy model. The data samples are brought into the entropy model to calculate the weights of each evaluation index of each industrial node. The calculation principle of the entropy weight is as follows: Assuming that the number of enterprises selected from the sample is n as the evaluated objects, 20 evaluation indicators are constructed, the entropy method is used to determine the weights of the indicators, and Python is used to build the algorithm. Let the jth index of the i-th evaluated object be x ij , then the evaluation index data forms a matrix A=x ij ) n×20 , which is generally called a decision matrix. The specific implementation steps of using the entropy method to determine the indicator weights are as follows:

[0043] (1) Dimensionless processing of evaluation index data

[0044] Considering that different evaluation index data of the evaluated object have different dimensions and dimensional units, the evaluation index data are dimensionless processed by using the efficacy coefficient transformation method, so as to make the evaluation index data comparable.

[0045] make:

[0046] y ij =[x ij -min(x 1j ,x 2j ,…,x nj )] / [max(x 1j ,x 2j ,…,x nj )-min(x 1j ,x 2j ,…,x nj )]+1

[0047] Where i = 1, 2, ..., n; j = 1, 2, ..., 20

[0048] After dimensionless processing, the actual data values ​​x of the 20 evaluation index data of n companies are converted into ij Convert to index evaluation value y ij .

[0049] (2) Transform the weight of each indicator evaluation value after dimensionless processing

[0050] Evaluation value y ij (i=1,2,…,n;j=1,2,…,20) perform weight transformation and obtain the index evaluation value p after weight transformation ij The calculation formula is:

[0051]

[0052] (3) Calculate the entropy value E of the evaluation index j

[0053] The evaluation value p of the 20 indexes after weight transformation of n companies ij The entropy value is calculated using the following formula:

[0054]

[0055] Where, j = 1, 2, ..., 20; K = 1 / lnn

[0056] (4) Calculate the coefficient of difference of evaluation indicators

[0057] Calculate the difference coefficient of the jth indicator of the evaluation index, and set the difference coefficient as d j , and its calculation formula is:

[0058] d j =1-E j , j=1,2,…,20

[0059] The larger the difference coefficient of the j-th indicator, the more important the j-th indicator is, and the entropy value E j The smaller it is.

[0060] (5) Calculate indicator weights

[0061] The coefficient of variation d j Normalized, as the weight of each indicator ω j , and its calculation formula is:

[0062]

[0063] In addition, the indicator weights can be determined by combining subjective and objective methods, that is, the objective evaluation method "entropy method" is mainly used to determine the weights. The entropy method is an objective weighting method. Its principle is to determine the weights according to the amount of information reflected by the degree of variation of the values ​​of each evaluation indicator. In addition, the subjective evaluation method "Delphi method" is also combined to adjust the weights. Using this subjective and objective weight determination method, different weights can be obtained by fully combining the characteristics of different industries. In addition, through weight adjustment, the impact of different weights on the score can be evaluated to ensure the robustness of the model.

[0064] In step S104, the strength evaluation result of the industrial node of the industrial chain is determined according to the strength score of the industrial node of the industrial chain.

[0065] In some optional embodiments, when determining the strength evaluation result of the industrial node of the industrial chain according to the strength score of the industrial node of the industrial chain, the strength score of the industrial node of the industrial chain is graded to obtain the grade of the strength score of the industrial node of the industrial chain; and the strength evaluation result of the industrial node of the industrial chain is determined according to the grade of the strength score of the industrial node of the industrial chain. Thus, the strength evaluation result of the industrial node of the industrial chain can be accurately determined according to the grade of the strength score of the industrial node of the industrial chain.

[0066] In a specific example, the strength of the industrial chain is divided into five levels: Level 1, Level 2, Level 3, Level 4 and Level 5. The thresholds and specific meanings of the levels are shown in the table below:

[0067]

[0068]

[0069] Table 2 Comparison table of classification thresholds and their meanings

[0070] Specifically, the variance and standard deviation in Table 2 can be calculated based on the strength scores of different evaluation areas at the same industrial chain node.

[0071] In some optional embodiments, the industrial nodes of the industrial chain include: the first-level industrial nodes of the industrial chain, the second-level industrial nodes of the industrial chain, and the third-level industrial nodes of the industrial chain, and the method further includes: calculating the strength score of the third-level industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial nodes of the industrial chain; calculating the strength score of the second-level industrial node of the industrial chain according to the strength score of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain and the weight of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain; calculating the strength score of the first-level industrial node of the industrial chain according to the strength score of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain and the weight of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain. Thus, the strength score of the second-level industrial node of the industrial chain can be accurately calculated through the strength score of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain and the weight of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain. In addition, the strength score of the first-level industrial node of the industrial chain can be accurately calculated through the strength score of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain and the weight of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain.

[0072] In a specific example, the object of the strength evaluation of the industrial chain is the industrial nodes at all levels of the industrial chain. For example, when the object of the strength evaluation of the industrial chain is the industrial nodes at all levels of the intelligent networked automobile industry chain, the first-level industrial nodes of the intelligent networked automobile industry chain can be automobile core parts production (upstream), automobile intelligent support system (midstream) and vehicle manufacturing and operation and maintenance (downstream), etc., the second-level industrial nodes of the intelligent networked automobile industry chain can be automobile transmission, automobile body, automobile transmission system, automobile electrical system, automobile electronic system, automobile driving system and automobile braking system, etc., and the third-level industrial nodes of the intelligent networked automobile industry chain can be planetary gears, clutches, synchronizers, differentials, torque converters and hydraulic oil pumps, etc. In addition, the evaluation is carried out starting from the last-level industrial node, and the strength score of the last-level node is synthesized according to the strength score of the last-level node. Each evaluation indicator is scored, then multiplied by the corresponding weight, and finally the weighted sum is obtained to obtain the score of each last-level industrial node. In actual operation, there is no unified standard for the weight setting and scoring of each evaluation indicator, which can be determined according to the data situation, and some evaluation indicators can be increased or decreased. Specifically, assuming that the industrial chain consists of three levels and the third level has 15 nodes, then the strength score CI of a node at the third level is i The calculation method of (i=1…15) adopts the linear weighting method, that is:

[0073]

[0074] Among them, λ n is the weight of each evaluation index, is the score value of each evaluation index. Assuming that the number of second-level nodes in the industrial chain is 5, then the strength score RI of the second-level nodes is i (i=1...5) is obtained by weighting the nodes of the third level under the second level node. Similarly, the score of the first level node is obtained by weighting the nodes of the second level under the first level node.

[0075] In a specific example, Figure 1BAs shown, the second enterprise indicator data of the enterprises within the evaluation area within the historical time period are extracted from multiple enterprise data sources, and the second enterprise indicator data of the enterprises within the evaluation area within the historical time period are cleaned to obtain the third enterprise indicator data of the enterprises within the evaluation area within the historical time period, and then the third enterprise indicator data of the enterprises within the evaluation area within the historical time period are fused to obtain the first enterprise indicator data of the enterprises within the evaluation area within the historical time period, and then the first enterprise indicator data of the enterprises within the evaluation area within the historical time period are stored in the data warehouse, and then, according to multiple evaluation indicators for evaluating the strength of industrial nodes of the industrial chain, the first enterprise indicator data of the enterprises within the evaluation area within the historical time period in the data warehouse are processed (feature engineering) to obtain multiple evaluation indicator data of multiple enterprises of the industrial nodes of the industrial chain, and based on the multiple evaluation indicator data of multiple enterprises of the industrial nodes of the industrial chain, model development is carried out, and the model can be put into operation after development. Specifically, based on multiple evaluation index data of multiple enterprises at the industrial nodes of the industrial chain, the thresholds of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and then based on the thresholds of the multiple evaluation indexes of the industrial nodes of the industrial chain, the scores of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and then based on the multiple evaluation index data of multiple enterprises at the industrial nodes of the industrial chain, the weights of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and then based on the weights and scores of the multiple evaluation indexes of the industrial nodes of the industrial chain, the strength score of the industrial node of the industrial chain is determined; finally, based on the strength score of the industrial node of the industrial chain, the strength evaluation result of the industrial node of the industrial chain is determined.

[0076] Through the evaluation method for the strength of an industrial chain provided in the embodiment of the present application, the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within a historical time period are processed according to multiple evaluation indicators for evaluating the strength of industrial nodes of the industrial chain to obtain multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, and based on the multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain are determined, and then based on the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain, the scores of the multiple evaluation indicators of the industrial node of the industrial chain are determined, so that the scores of the multiple evaluation indicators of the industrial node of the industrial chain can be accurately determined. In addition, based on the multiple evaluation index data of multiple enterprises at the industrial nodes of the industrial chain, the weights of the multiple evaluation indexes of the industrial nodes of the industrial chain are determined, and based on the weights and scores of the multiple evaluation indexes of the industrial nodes of the industrial chain, the strength score of the industrial node of the industrial chain is determined. Based on the strength score of the industrial node of the industrial chain, the strength evaluation result of the industrial node of the industrial chain can be accurately determined, and then the strength of the industrial nodes of the industrial chain can be effectively evaluated to reflect the strength of the industrial nodes of the industrial chain.

[0077] The evaluation method for the strength of the industrial chain provided in this embodiment can be executed by any appropriate device with data processing capabilities, including but not limited to: cameras, terminals, mobile terminals, PCs, servers, vehicle-mounted equipment, entertainment equipment, advertising equipment, personal digital assistants (PDAs), tablet computers, laptop computers, handheld game consoles, smart glasses, smart watches, wearable devices, virtual display devices or display enhancement devices (such as Google Glass, Oculus Rift, Hololens, GearVR), etc.

[0078] Reference Figure 2 , showing a schematic diagram of the structure of the device for evaluating the strength of the industrial chain in the second embodiment of the present application.

[0079] The evaluation device for the strength of an industrial chain provided in this embodiment includes: a processing module 201, which is used to process the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within a historical time period according to multiple evaluation indicators for evaluating the strength of an industrial node of an industrial chain, so as to obtain multiple evaluation indicator data of multiple enterprises of the industrial node of the industrial chain; a first determination module 202, which is used to determine the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the scores of the multiple evaluation indicators of the industrial node of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain; a second determination module 203, which is used to determine the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the strength score of the industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain; a third determination module 204, which is used to determine the strength evaluation result of the industrial node of the industrial chain according to the strength score of the industrial node of the industrial chain.

[0080] Optionally, before the processing module 201, the device also includes: an extraction module, used to extract the second enterprise indicator data of the enterprises within the evaluation area within the historical time period from multiple enterprise data sources; a data cleaning module, used to clean the second enterprise indicator data of the enterprises within the evaluation area within the historical time period to obtain the third enterprise indicator data of the enterprises within the evaluation area within the historical time period; a data fusion module, used to fuse the third enterprise indicator data of the enterprises within the evaluation area within the historical time period to obtain the first enterprise indicator data of the enterprises within the evaluation area within the historical time period; a storage module, used to store the first enterprise indicator data of the enterprises within the evaluation area within the historical time period in the data warehouse.

[0081] Optionally, the data cleaning module is specifically used to: use a missing value filling method to process the missing values ​​of the second enterprise indicator data of the enterprises within the evaluation area within the historical time period; use a clustering algorithm to cluster the second enterprise indicator data after the missing value processing to obtain the clustering results of the second enterprise indicator data after the missing value processing; based on the clustering results, identify the abnormal values ​​in the second enterprise indicator data after the missing value processing, and eliminate the abnormal values ​​to obtain the third enterprise indicator data of the enterprises within the evaluation area within the historical time period.

[0082] Optionally, the processing module 201 is specifically used to: filter the first enterprise indicator data according to the multiple evaluation indicators to obtain the filtered first enterprise indicator data; and determine multiple evaluation indicator data of multiple enterprises at the industrial nodes of the industrial chain according to the filtered first enterprise indicator data.

[0083] Optionally, the first determination module 202 is specifically used to: determine the distribution status of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain; determine the threshold of the same evaluation index of the industrial node of the industrial chain based on the distribution status of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain and a preset distribution ratio.

[0084] Optionally, the first determination module 202 is specifically used to: determine the mean and standard deviation of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain; determine the threshold of the same evaluation index of the industrial node of the industrial chain based on the mean and standard deviation of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain.

[0085] Optionally, the first determination module 202 is specifically used to: determine the threshold interval of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the threshold values ​​of the multiple evaluation indicators of the industrial nodes of the industrial chain; determine the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the threshold intervals of the multiple evaluation indicators of the industrial nodes of the industrial chain.

[0086] Optionally, the second determination module 203 includes: a sampling submodule, used to sample multiple evaluation index data of multiple enterprises in the industrial nodes of the industrial chain by adopting a stratified random sampling method; and a determination submodule, used to determine the weights of the multiple evaluation indexes of the industrial nodes of the industrial chain based on the multiple evaluation index data of the multiple enterprises in the industrial nodes of the industrial chain after sampling.

[0087] Optionally, the determination submodule is specifically used to: use the power coefficient transformation method to perform dimensionless processing on the multiple evaluation index data of the multiple enterprises in the industrial nodes of the industrial chain after sampling; perform weight transformation on the multiple evaluation index data of the multiple enterprises in the industrial nodes of the industrial chain that have been dimensionless processed; calculate the entropy value of the multiple evaluation indexes of the industrial nodes of the industrial chain based on the multiple evaluation index data of the multiple enterprises in the industrial nodes of the industrial chain after the weight transformation; calculate the difference coefficient of the multiple evaluation indexes of the industrial nodes of the industrial chain based on the entropy value of the multiple evaluation indexes of the industrial nodes of the industrial chain; normalize the difference coefficient of the multiple evaluation indexes of the industrial nodes of the industrial chain to obtain the weights of the multiple evaluation indexes of the industrial nodes of the industrial chain.

[0088] Optionally, the industrial nodes of the industrial chain include: the first-level industrial nodes of the industrial chain, the second-level industrial nodes of the industrial chain and the third-level industrial nodes of the industrial chain, and the device also includes: a first calculation module, used to calculate the strength score of the third-level industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial nodes of the industrial chain; a second calculation module, used to calculate the strength score of the second-level industrial node of the industrial chain according to the strength score of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain and the weight of the third-level industrial node of the industrial chain under the second-level industrial node of the industrial chain; a third calculation module, used to calculate the strength score of the first-level industrial node of the industrial chain according to the strength score of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain and the weight of the second-level industrial node of the industrial chain under the first-level industrial node of the industrial chain.

[0089] Optionally, the third determination module 204 is specifically used to: classify the strength scores of the industrial nodes of the industrial chain to obtain the level of the strength scores of the industrial nodes of the industrial chain; and determine the strength evaluation results of the industrial nodes of the industrial chain according to the level of the strength scores of the industrial nodes of the industrial chain.

[0090] Optionally, the multiple evaluation indicators include at least one of the following: the scale and operating strength of the industrial chain, the R&D and innovation capabilities of the industrial chain, the strength of listed companies in the industrial chain, and the robustness of the industrial chain supply chain.

[0091] Optionally, the scale and operating strength of the industrial chain include at least one of the following: the logarithm of the sum of the mean output and the mean sales volume, the mean output, the proportion of output value to regional GDP, and the logarithm of the sum of registered capital; and / or, the R&D and innovation capabilities of the industrial chain include at least one of the following: the average year-on-year change rate of invention patent applications in the past three years, the average year-on-year change rate of patent applications in the past three years, the average year-on-year change rate of the number of patent applicants in the past three years, the average year-on-year change rate of trademark registrations in the past three years, and the average year-on-year change rate of the number of copyrights in the past three years; and / or, the strength of listed companies in the industrial chain includes at least one of the following: the total share capital of listed companies in the industrial chain, the total revenue of listed companies in the industrial chain, the total assets of listed companies in the industrial chain, the total net profit of listed companies in the industrial chain, the total number of employees of listed companies in the industrial chain, the intensity of R&D funding investment of listed companies, the proportion of master and doctoral students in listed companies, the average accounts receivable turnover rate of listed companies in the industrial chain, and the average accounts payable turnover rate of listed companies in the industrial chain; and / or, the robustness of the supply chain of the industrial chain includes at least one of the following: the ratio of the number of upstream and downstream companies in the industrial supply chain, and the ratio of the transaction value of upstream and downstream companies in the industrial supply chain.

[0092] The device for evaluating the strength of an industrial chain provided in this embodiment is used to implement the corresponding evaluation methods for the strength of an industrial chain in the aforementioned multiple method embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0093] Figure 3 This is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present application; the electronic device may include:

[0094] One or more processors 301;

[0095] The computer readable medium 302 may be configured to store one or more programs,

[0096] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating the strength of the industrial chain as described in the first embodiment.

[0097] Figure 4 The hardware structure of the electronic device in the fourth embodiment of the present application; Figure 4 As shown, the hardware structure of the electronic device may include: a processor 401, a communication interface 402, a computer readable medium 403 and a communication bus 404;

[0098] The processor 401, the communication interface 402, and the computer readable medium 403 communicate with each other via a communication bus 404;

[0099] Optionally, the communication interface 402 may be an interface of a communication module, such as an interface of a GSM module;

[0100] Among them, the processor 401 can be specifically configured as: according to multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain, the first enterprise indicator data of the enterprises within the evaluation area in the data warehouse within the historical time period is processed to obtain multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain; according to the multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain are determined, and according to the threshold values ​​of the multiple evaluation indicators of the industrial node of the industrial chain, the scores of the multiple evaluation indicators of the industrial node of the industrial chain are determined; according to the multiple evaluation indicator data of multiple enterprises in the industrial node of the industrial chain, the weights of the multiple evaluation indicators of the industrial node of the industrial chain are determined, and according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain, the strength score of the industrial node of the industrial chain is determined; according to the strength score of the industrial node of the industrial chain, the strength evaluation result of the industrial node of the industrial chain is determined.

[0101] The processor 401 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may 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 gate or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0102] The computer readable medium 403 can be, but is not limited to, a random access memory medium (RAM), a read-only memory medium (ROM), a programmable read-only memory medium (PROM), an erasable programmable read-only memory medium (EPROM), an electrically erasable read-only memory medium (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

[0103] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code configured to execute the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the present application are executed. It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access storage medium (RAM), a read-only storage medium (ROM), an erasable programmable read-only storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only storage medium (CD-ROM), an optical storage medium, a magnetic storage medium, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program configured to be used by or in combination with an instruction execution system, an apparatus or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0104] Computer program code configured to perform the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0105] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of the code contains one or more executable instructions configured to implement the specified logical function. There are specific sequential relationships in the above-mentioned specific embodiments, but these sequential relationships are only exemplary. When the specific implementation is implemented, these steps may be less, more, or the execution order may be adjusted. That is, in some implementations as replacements, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] The modules involved in the embodiments of the present application may be implemented in software or in hardware. The modules described may also be provided in a processor, for example, may be described as: a processor including a processing module, a first determination module, a second determination module, and a third determination module. Among them, the names of these modules do not constitute a limitation on the module itself under certain circumstances. For example, the processing module may also be described as "a module for processing the first enterprise index data of enterprises within the evaluation area in the data warehouse within a historical time period according to multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain, so as to obtain multiple evaluation index data of multiple enterprises of the industrial nodes of the industrial chain".

[0107] As another aspect, the present application further provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the method for evaluating the strength of an industrial chain as described in the above-mentioned embodiment 1 is implemented.

[0108] As another aspect, the present application further provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the device, the device: processes the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within a historical time period according to multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain to obtain multiple evaluation indicator data of multiple enterprises in the industrial nodes of the industrial chain; determines the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises in the industrial nodes of the industrial chain, and determines the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain; determines the weights of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises in the industrial nodes of the industrial chain, and determines the strength score of the industrial nodes of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial nodes of the industrial chain; determines the strength evaluation result of the industrial nodes of the industrial chain according to the strength score of the industrial nodes of the industrial chain.

[0109] The expressions "first", "second", "the first" or "the second" used in various embodiments of the present disclosure may modify various components regardless of order and / or importance, but these expressions do not limit the corresponding components. The above expressions are only configured for the purpose of distinguishing an element from other elements. For example, a first user device and a second user device represent different user devices, although both are user devices. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element without departing from the scope of the present disclosure.

[0110] When one element (e.g., a first element) is referred to as being "(operably or communicatively) coupled" or "(operably or communicatively) coupled to" or "connected to" another element (e.g., a second element), it is understood that the one element is directly connected to the other element or the one element is indirectly connected to the other element via yet another element (e.g., a third element). Conversely, it is understood that when an element (e.g., a first element) is referred to as being "directly connected" or "directly coupled" to another element (the second element), no element (e.g., a third element) is interposed between the two.

[0111] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above invention concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A method for evaluating the strength of an industrial chain, characterized in that: The method comprises: According to multiple evaluation indicators for evaluating the strength of industrial nodes of the industrial chain, the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within the historical time period are processed to obtain multiple evaluation indicator data of multiple enterprises of the industrial nodes of the industrial chain; Determine the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the scores of the multiple evaluation indicators of the industrial node of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain; Determine the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the strength score of the industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain. When determining the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling, use the power coefficient transformation method to perform dimensionless processing on the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling; perform weight transformation on the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after dimensionless processing; calculate the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after weight transformation; calculate the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial chain according to the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain; normalize the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial node of the industrial chain to obtain the weights of the multiple evaluation indicators of the industrial node of the industrial chain; According to the strength scores of the industrial nodes of the industrial chain, the strength evaluation results of the industrial nodes of the industrial chain are determined.

2. The method for evaluating the strength of an industrial chain according to claim 1, characterized in that: Before processing the first enterprise indicator data of enterprises within the evaluation area in the data warehouse within the historical time period according to the multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain, the method further includes: Extracting second enterprise indicator data of enterprises within the evaluation area within the historical time period from multiple enterprise data sources; Performing data cleaning on the second enterprise index data of the enterprises within the evaluation area within the historical time period to obtain the third enterprise index data of the enterprises within the evaluation area within the historical time period; Performing data fusion on the third enterprise index data of the enterprises within the evaluation area within the historical time period to obtain the first enterprise index data of the enterprises within the evaluation area within the historical time period; The first enterprise index data of the enterprises within the evaluation area within the historical time period is stored in the data warehouse.

3. The method for evaluating the strength of an industrial chain according to claim 2, characterized in that: The data cleaning of the second enterprise indicator data of the enterprises within the evaluation area within the historical time period includes: Using a missing value filling method, processing the missing values ​​of the second enterprise indicator data of the enterprises within the evaluation area within the historical time period; Using a clustering algorithm, clustering the second enterprise indicator data after the missing value processing is performed to obtain a clustering result of the second enterprise indicator data after the missing value processing; According to the clustering result, outliers in the second enterprise indicator data after missing value processing are identified, and the outliers are eliminated to obtain third enterprise indicator data of the enterprises within the evaluation area within the historical time period.

4. The method for evaluating the strength of an industrial chain according to claim 1, characterized in that: The processing of the first enterprise index data of the enterprises within the evaluation area in the data warehouse within the historical time period according to the multiple evaluation indicators for evaluating the strength of the industrial nodes of the industrial chain includes: According to the multiple evaluation indicators, the first enterprise indicator data is screened to obtain the screened first enterprise indicator data; Based on the screened first enterprise indicator data, multiple evaluation indicator data of multiple enterprises at the industrial nodes of the industrial chain are determined.

5. The method for evaluating the strength of an industrial chain according to claim 1, characterized in that: Determining the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial nodes of the industrial chain includes: Determine the distribution status of evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain; According to the distribution status and preset distribution ratio of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain, the threshold value of the same evaluation index of the industrial node of the industrial chain is determined.

6. The method for evaluating the strength of an industrial chain according to claim 1, characterized in that: Determining the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial nodes of the industrial chain includes: Determine the mean and standard deviation of the evaluation index data of the same evaluation index of multiple enterprises in the industrial node of the industrial chain; A threshold value of the same evaluation indicator of the industrial node of the industrial chain is determined according to the mean and standard deviation of the evaluation indicator data of the same evaluation indicator of multiple enterprises in the industrial node of the industrial chain.

7. The method for evaluating the strength of an industrial chain according to claim 1, characterized in that: Determining the scores of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain includes: Determining the threshold ranges of the multiple evaluation indicators of the industrial nodes of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial nodes of the industrial chain; The scores of the multiple evaluation indicators of the industrial nodes of the industrial chain are determined according to the threshold ranges of the multiple evaluation indicators of the industrial nodes of the industrial chain.

8. A device for evaluating the strength of an industrial chain, characterized in that: The device comprises: A processing module, for processing first enterprise index data of enterprises within the evaluation area in the data warehouse within a historical time period according to multiple evaluation indexes for evaluating the strength of industrial nodes of the industrial chain, so as to obtain multiple evaluation index data of multiple enterprises of the industrial nodes of the industrial chain; A first determination module is used to determine the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the scores of the multiple evaluation indicators of the industrial node of the industrial chain according to the thresholds of the multiple evaluation indicators of the industrial node of the industrial chain. When determining the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling, use the power coefficient transformation method to perform dimensionless processing on the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after sampling; perform weight transformation on the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after dimensionless processing; calculate the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain after weight transformation; calculate the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial chain according to the entropy value of the multiple evaluation indicators of the industrial node of the industrial chain; normalize the difference coefficient of the multiple evaluation indicators of the industrial node of the industrial chain to obtain the weights of the multiple evaluation indicators of the industrial node of the industrial chain; A second determination module is used to determine the weights of the multiple evaluation indicators of the industrial node of the industrial chain according to the multiple evaluation indicator data of the multiple enterprises of the industrial node of the industrial chain, and determine the strength score of the industrial node of the industrial chain according to the weights and scores of the multiple evaluation indicators of the industrial node of the industrial chain; The third determination module is used to determine the strength evaluation result of the industrial node of the industrial chain according to the strength score of the industrial node of the industrial chain.

9. An electronic device, characterized in that: The device comprises: one or more processors; A computer-readable medium is configured to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating the strength of the industrial chain as described in any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for evaluating the strength of an industrial chain as described in any one of claims 1 to 7 is implemented.

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