CN113869768A - Method, device, equipment and readable medium for evaluating strength of industrial chain - Google Patents

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

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CN113869768A
CN113869768A CN202111182517.3A CN202111182517A CN113869768A CN 113869768 A CN113869768 A CN 113869768A CN 202111182517 A CN202111182517 A CN 202111182517A CN 113869768 A CN113869768 A CN 113869768A
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enterprises
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吴楠
王建健
王巍
杨凯华
齐海茂
舒南飞
王程
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I Xinnuo Credit Co ltd
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Abstract

The embodiment of the application provides an evaluation method, device and equipment for industrial chain strength and readable media. Wherein the method comprises the following steps: according to the multiple evaluation indexes, enterprise index data of enterprises in the evaluation area range in a historical time period are processed, and multiple evaluation index data of multiple enterprises of the industrial node are obtained; determining threshold values of a plurality of evaluation indexes of an industrial node according to a plurality of evaluation index data of a plurality of enterprises of the industrial node, and determining scores of the plurality of evaluation indexes of the industrial node of an industrial chain according to the threshold values; determining weights of a plurality of evaluation indexes of the industrial node according to a plurality of evaluation index data of a plurality of enterprises of the industrial node, and determining a strength score of the industrial node according to the weights and the score; and determining the strength evaluation result of the industrial node according to the strength score of the industrial node. The method and the system can effectively evaluate the strength of the industrial nodes of the industrial chain so as to reflect the strength of the industrial nodes of the industrial chain.

Description

Method, device, equipment and readable medium for evaluating strength of industrial chain
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to an evaluation method and device for industrial chain strength, an electronic device and a computer readable medium.
Background
At present, although the development of strategic emerging industries in China is fast, certain links of neck clamping and chain dropping still exist. The traditional industries of energy, electricity, petroleum, petrifaction, steel, nonferrous metal and the like face industrial transformation and upgrading so as to adapt to the ever-changing changes of domestic and foreign economic forms. In some key fields, core technologies do not reach complete autonomous controllability, and the height required by new and old kinetic energy conversion and industrial structure upgrading is not yet completely reached. Supporting the development of related industries, governments should play a leading role and provide necessary policy support, and due to the lack of deep understanding of the development conditions of the industries, the construction of related supervision modes and law and regulation systems still lags behind the actual conditions. The evaluation of the strength of the industrial chain is helpful for fully and visually knowing the development condition of each industrial node of the industrial chain, and the development level of the regional industry is continuously improved and the balanced development of the industry is promoted by building the chain, extending the chain, supplementing the chain and strengthening the chain. In addition, in the industry chain recruitment work, related organizations and personnel need to know the development conditions of the local industry chain and each industry node of the industry chain so as to better establish recruitment policies and establish industry development plans, however, an evaluation method for the strength of the industry chain is still lacking in China.
Therefore, 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 to be solved at present.
Disclosure of Invention
The present application is directed to a method and an apparatus for evaluating strength of an industrial chain, an electronic device, and a computer readable medium, which are used to solve the technical problem in the prior art of how to effectively evaluate strength of an industrial node of an industrial chain to reflect strength of the industrial node of the industrial chain.
According to a first aspect of the embodiments of the present application, a method for evaluating the strength of an industrial chain is provided. The method comprises the following steps: processing first enterprise index data of enterprises in an evaluation area range in a data warehouse within a historical time period according to a plurality of evaluation indexes for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain; determining threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain, and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain; determining weights of the evaluation indexes of the enterprises of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determining strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain; and determining 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.
According to a second aspect of the embodiments of the present application, there is provided an apparatus for evaluating the strength of an industrial chain. The device comprises: the processing module is used for processing first enterprise index data of enterprises in an evaluation area range in a data warehouse in a historical time period according to a plurality of evaluation indexes used for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain; a first determining module, configured to determine threshold values of the plurality of evaluation indexes of an industrial node of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain, and determine scores of the plurality of evaluation indexes of the industrial node of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain; a second determining module, configured to determine weights of the evaluation indexes of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determine strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain; and the third determining module is used for determining the strength evaluation result of the industrial nodes of the industrial chain according to the strength scores of the industrial nodes of the industrial chain.
According to a third aspect of embodiments of the present application, there is provided an electronic apparatus, including: one or more processors; a computer readable medium configured to store one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method for evaluating the strength of an industry chain as described in the first aspect of the embodiments above.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements the method for evaluating the strength of an industrial chain as described in the first aspect of the embodiments above.
According to the evaluation scheme of the industrial chain strength, the first enterprise index data of enterprises in the evaluation area range in the data warehouse in the historical time period is processed according to the plurality of evaluation indexes for evaluating the strength of the industrial nodes of the industrial chain, so as to obtain the plurality of evaluation index data of the plurality of enterprises of the industrial nodes of the industrial chain, the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain are determined according to the plurality of evaluation index data of the plurality of enterprises of the industrial nodes of the industrial chain, the scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain are determined according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain, and the scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain can be accurately determined. In addition, the weights of the evaluation indexes of the industrial nodes of the industrial chain are determined according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, the strength score of the industrial node of the industrial chain is determined according to the weights and the scores of the evaluation indexes of the industrial nodes of the industrial chain, and the strength evaluation result of the industrial node of the industrial chain can be accurately determined according to the strength score of the industrial node of the industrial chain, so that the strength of the industrial node of the industrial chain can be effectively evaluated to reflect the strength of the industrial node of the industrial chain.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1A is a flowchart illustrating steps of a method for evaluating strength of an industrial chain according to an embodiment of the present disclosure;
fig. 1B is a flowchart illustrating steps of a method for evaluating strength of an industrial chain according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an apparatus for evaluating strength of an industrial chain according to a second embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device in a third embodiment of the present application;
fig. 4 is a hardware structure of an electronic device according to a fourth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Referring to fig. 1A, a flowchart of the steps of the method for evaluating the strength of an industry chain in the first embodiment of the present application is shown.
Specifically, the method for evaluating the strength of the industrial chain provided by the embodiment of the application comprises the following steps:
in step S101, first enterprise index data of enterprises within an evaluation area range in a data warehouse within a historical time period is processed according to a plurality of evaluation indexes for evaluating the strengths and weaknesses of industrial nodes of an industrial chain, so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain.
In this embodiment, the industrial chain may be an intelligent networked automobile industrial chain, the industrial nodes may be automobile core component production (upstream), automobile transmission, automobile body, automobile transmission system, automobile electrical system, planetary gear, clutch, synchronizer, differential, hydraulic torque converter, hydraulic oil pump, etc., and the evaluation area range may be provincial, autonomous, direct prefecture, and prefecture. The evaluation index data can be understood as a numerical value of the evaluation index. The plurality of evaluation indicators include at least one of: the scale and the operation strength of the industrial chain, the research and development innovation capability of the industrial chain, the market enterprise strength of the industrial chain and the stability of the supply chain of the industrial chain. The industry chain scale and business practices include at least one of: logarithm of the sum of the production mean and the sales mean, logarithm of the production mean, GDP specific gravity of the production value in the region, and logarithm of the registered capital sum; and/or, the industry chain development innovation capability comprises at least one of: the patent application amount average same-proportion change rate invented in last three years, the patent application number average same-proportion change rate invented in last three years, the trademark registration amount average same-proportion change rate invented in last three years, the copyright number average same-proportion change rate invented in last three years; and/or, the industry chain marketing enterprise capability comprises at least one of: the method comprises the following steps of (1) total stock book of enterprises on which the industrial chain is listed, total revenue income of enterprises on which the industrial chain is listed, total assets of enterprises on which the industrial chain is listed, net profit total of enterprises on which the industrial chain is listed, total employee number of enterprises on which the industrial chain is listed, research and development expense investment intensity of the enterprises on which the industrial chain is listed, proportion of persons on which the enterprises on which the industrial chain is listed, average receivable account turnover rate of the enterprises on which the industrial chain is listed and average payable account turnover rate of the enterprises on which the industrial chain is listed; and/or, the industry chain supply chain robustness comprises at least one of: the ratio of the number of enterprises on the upstream and downstream of the industry supply chain, and the ratio of the trading value on the upstream and downstream of the industry supply chain. On the whole, an index system is constructed from four parts, namely the scale and the operation strength of an industrial chain, the research and development innovation capability of the industrial chain, the market enterprise strength of the industrial chain and the stability of a supply chain of the industrial chain, the dimensionality of the index system is richer and more comprehensive, and the strength of an industrial node of the industrial chain is evaluated in an all-round manner.
Specifically, the index system is shown in table 1 below:
Figure BDA0003297844610000051
Figure BDA0003297844610000061
TABLE 1 INDUSTRIAL CHAIN STRENGTH-WEIGHT INDICATOR SYSTEM TABLE
The method comprises the steps of calculating the registered capital indexes, considering the problem of the established years of different enterprises, and adopting a weighted summation method. The enterprises are classified into different ages (within 1 year, 1-3 years, 3-5 years, 5-7 years, 7-10 years and more than 10 years), different weights are given to the enterprises of different ages, and logarithms are obtained after linear weighting summation. The production average, the production average and the sales average are averaged using data from 2 to 3 years ago.
In some optional embodiments, before processing the first enterprise index data of the enterprises in the evaluation area range in the data warehouse within the historical time period according to a plurality of evaluation indexes for evaluating the strengths and weaknesses of the industrial nodes of the industrial chain, the method further includes: extracting second enterprise index data of enterprises in the evaluation area range in the historical time period from a plurality of enterprise data sources; performing data cleaning on second enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain third enterprise index data of the enterprises in the evaluation area range in the historical time period; performing data fusion on the third enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain first enterprise index data of the enterprises in the evaluation area range in the historical time period; storing first enterprise index data of enterprises within the evaluation area range in the historical time period into the data warehouse. The second enterprise index data may be original enterprise index data, the third enterprise index data may be cleaned enterprise index data, and the first enterprise index data may be merged enterprise index data. Thereby, the first enterprise index data of the enterprises in the evaluation area range in the historical time period can be effectively stored in the data warehouse.
In a specific example, when data cleaning is performed on the second enterprise index data of the enterprise in the evaluation area range in the historical time period, missing value processing is performed on the second enterprise index data of the enterprise in the evaluation area range in the historical time period in a missing value completion mode; clustering the second enterprise index data subjected to the missing value processing by adopting a clustering algorithm to obtain a clustering result of the second enterprise index data subjected to the missing value processing; and according to the clustering result, identifying abnormal values in the second enterprise index data subjected to missing value processing, and removing the abnormal values to obtain third enterprise index data of enterprises in the evaluation area range in the historical time period. Thereby, the third enterprise index data of the enterprises in the evaluation area range in the historical time period can be effectively obtained.
In one specific example, a common deficiency completion method: mean interpolation, homogeneous mean interpolation, modeling prediction, high-dimensional mapping, multiple interpolation, maximum likelihood estimation and the like. The missing value processing in the model adopts a similar mean interpolation method to process the missing value, firstly, the data is marked with the label of an industrial node, and then the mean value of the samples in the industrial node is used for interpolating the missing value. In addition, outliers refer to sample points where some values in the sample deviate significantly from the rest of the values, and are therefore also referred to as outliers. The outlier elimination is to find out the outliers by using a clustering algorithm and then eliminate the outliers.
In a specific example, when data fusion is performed on the third enterprise index data of the enterprise in the evaluation area range in the historical time period, the third enterprise index data of the enterprise in the evaluation area range in the historical time period is statistically aggregated through the association field of the enterprise to obtain the first enterprise index data of the enterprise in the evaluation area range in the historical time period.
In some optional embodiments, when first enterprise index data of enterprises in an evaluation area range in a data warehouse in a historical time period is processed according to a plurality of evaluation indexes for evaluating the strength of industrial nodes of an industrial chain, the first enterprise index data is screened according to the plurality of evaluation indexes to obtain the screened first enterprise index data; and determining a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain according to the screened first enterprise index data. Therefore, the plurality of evaluation index data of the plurality of enterprises of the industrial nodes of the industrial chain can be accurately determined through the screened first enterprise index data.
In step S102, threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain are determined based on the plurality of evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, and scores of the plurality of evaluation indexes of the industrial node of the industrial chain are determined based on the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain.
In some optional embodiments, when determining the threshold values of the multiple evaluation indexes of the industrial nodes of the industrial chain according to the multiple evaluation index data of the multiple enterprises of the industrial nodes of the industrial chain, determining the distribution condition of the evaluation index data of the same evaluation index of the multiple enterprises of the industrial nodes of the industrial chain; determining a threshold value of the same evaluation index of the industrial nodes of the industrial chain according to the distribution state and the preset distribution proportion of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain. Thereby, the threshold value of the same evaluation index of an industrial node of the industrial chain can be accurately determined.
In a specific example, the graph method is to plot sample data of each evaluation index on a graph, and then determine an early warning control line according to the distribution condition 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 interval should be: [ 92% quantile, 100% quantile ], excellent; [ 80% quantile, 92% quantile), good; [ 20% quantile, 80% quantile), generally; [ 8% quantile, 20% quantile), poor; [ 0% quantile, 8% quantile), difference.
In some optional embodiments, when determining the threshold values of the evaluation indexes of the plurality of enterprises of the industrial node of the industrial chain according to the evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, determining a mean value and a standard deviation of the evaluation index data of the same evaluation index of the plurality of enterprises of the industrial node of the industrial chain; and determining the threshold value of the same evaluation index of the industrial node of the industrial chain according to the mean value and the standard deviation of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial node of the industrial chain. Thereby, the threshold value of the same evaluation index of an industrial node of the industrial chain can be accurately determined by the mean value and the standard deviation of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial node of the industrial chain.
In a specific example, the mean-standard deviation method is to calculate the sample mean μ and the sample standard deviation σ of each evaluation index from the data of each evaluation index, and then calculate μ -2 σ, μ - σ, μ, μ + σ, and μ +2 σ, respectively, and use these five values as threshold values.
In one specific example, the threshold determination method falls into two broad categories: one is a subjective empirical method, such as a growth rate determination method, a graphical method, etc.; one type is a relatively objective data-based quantitative method, such as the mean-standard deviation method. The threshold value is determined through a step-by-step searching, adjusting and optimizing process, the threshold value is not constant but changes along with the stage development of the economic operation situation, and the usability problem of the historical empirical data under a new environment is particularly noticed. The threshold is preferably determined by a combination of qualitative and quantitative analysis, subjective and objective.
In some optional embodiments, when determining the scores of the plurality of evaluation indexes of an industry node of the industry chain according to the threshold values of the plurality of evaluation indexes of the industry node of the industry chain, determining the threshold intervals of the plurality of evaluation indexes of the industry node of the industry chain according to the threshold values of the plurality of evaluation indexes of the industry node of the industry chain; and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold value intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain. Accordingly, the scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain can be accurately determined through the threshold intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain.
In step S103, weights of the plurality of evaluation indexes of the plurality of enterprises of the industrial node of the industrial chain are determined based on the plurality of evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, and a strength score of the industrial node of the industrial chain is determined based on the weights and scores of the plurality of evaluation indexes of the industrial node of the industrial chain.
In some optional embodiments, when determining the weights of the evaluation indexes of the enterprises of the industrial node of the industrial chain according to the evaluation index data of the enterprises of the industrial node of the industrial chain, sampling the evaluation index data of the enterprises of the industrial node of the industrial chain in a layered random sampling manner; and determining the weights of the evaluation indexes of the industrial nodes of the industrial chain according to the sampled evaluation index data of the enterprises of the industrial nodes of the industrial chain. Therefore, the weights of the evaluation indexes of the industrial nodes of the industrial chain can be accurately determined through the sampled evaluation index data of the enterprises of the industrial nodes of the industrial chain.
In a specific example, when determining the weights of the evaluation indexes of the plurality of enterprises of the industrial node of the industrial chain based on the sampled evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, the sampled evaluation index data of the plurality of enterprises of the industrial node of the industrial chain is subjected to dimensionless processing by using a power efficiency coefficient transformation method; performing weight transformation on a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain subjected to non-dimensionalization processing; calculating entropy values of a plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain after the proportion transformation; calculating difference coefficients of the evaluation indexes of the industrial nodes of the industrial chain according to entropy values of the evaluation indexes of the industrial nodes of the industrial chain; and normalizing the difference coefficients of the plurality of evaluation indexes of the industrial nodes of the industrial chain to obtain the weights of the plurality of evaluation indexes of the industrial nodes of the industrial chain. Therefore, the weights of the evaluation indexes of the industrial nodes of the industrial chain can be accurately obtained through the entropy values of the evaluation indexes of the industrial nodes of the industrial chain.
In a specific example, each industry chain first obtains data samples by means of hierarchical random sampling, and then constructs an entropy model. And substituting the data samples into an entropy method model to calculate the weight of each evaluation index of each industrial node. The principle of the entropy weight calculation is as follows: assuming that the number of enterprises selected by the sample is n as an evaluated object, 20 evaluation indexes are constructed, the weight of the indexes is determined by using an entropy method, and the evaluation is realized by using a Python construction algorithm. Let the i-th evaluated object's j-item be marked as xijThe evaluation index data form a matrix a of n rows and 20 columns, xij)n×20It is generally referred to as a decision matrix. The specific implementation steps for determining the index weight by using the entropy method are as follows:
(1) non-dimensionalization processing of evaluation index data
Considering that different evaluation index data of an evaluated object have different dimensions and dimension units, the evaluation index data are subjected to non-dimensionalization processing by using an efficacy coefficient transformation method, so that the evaluation index data have comparability.
Order:
yij＝[xij-min(x1j,x2j,…,xnj)]/[max(x1j,x2j,…,xnj)-min(x1j,x2j,…,xnj)]+1
wherein i is 1,2, …, n; j-1, 2, …,20
After 20 evaluation index data of n enterprises are subjected to dimensionless processing, the actual data values x of the evaluation index data are obtainedijConversion into index evaluation value yij。
(2) Carrying out proportion transformation on each index evaluation value subjected to dimensionless processing
Evaluation value y for indexij(i-1, 2, …, n; j-1, 2, …,20) and obtaining index evaluation value p after specific gravity transformationij. The calculation formula is as follows:
Figure BDA0003297844610000111
(3) calculating an entropy value E of an evaluation indexj
Index evaluation value p after 20 specific gravities of n enterprises are transformedijCarrying out entropy calculation, wherein the calculation formula is as follows:
Figure BDA0003297844610000112
wherein j is 1,2, …, 20; k1/lnn
(4) Calculating a difference coefficient of the evaluation index
Calculating the difference coefficient of the j index of the evaluation index, and setting the difference coefficient as djThe calculation formula is as follows:
dj＝1-Ej，j＝1,2,…,20
the larger the difference coefficient of the j index is, the more important the j index is, and the entropy value E isjThe smaller.
(5) Calculating the weight of the index
For coefficient of difference djNormalized as the weight ω of each indexjThe calculation formula is as follows:
Figure BDA0003297844610000121
in addition, the index weight can be determined in a mode of combining subjective and objective, namely, an objective evaluation method of an entropy method is mainly adopted to determine the weight. The entropy method is an objective weighting method, and the principle is to determine the weight according to the information quantity reflected by the variation degree of each evaluation index value. In addition, the weight is adjusted by combining with a subjective evaluation method of "delphire method". By using the subjective and objective combined weight determination mode, different weights can be obtained by fully combining the characteristics of different industries, and in addition, the influence of the different weights on the score is evaluated through weight adjustment so as to ensure the robustness of the model.
In step S104, the strength evaluation result of the industrial node of the industrial chain is determined based on the strength score of the industrial node of the industrial chain.
In some optional embodiments, when determining the strength evaluation result of an industry node of the industry chain according to the strength score of the industry node of the industry chain, the strength score of the industry node of the industry chain is graded to obtain a gear where the strength score of the industry node of the industry chain is located; and determining the strength evaluation result of the industrial nodes of the industrial chain according to the gear of the strength score of the industrial nodes of the industrial chain. Therefore, the strength evaluation result of the industrial nodes of the industrial chain can be accurately determined according to the gear of the strength score of the industrial nodes of the industrial chain.
In one specific example, the industry chain strength scores are divided into five grades: level 1, Level 2, Level 3, Level4 and Level 5. The thresholds and specific meanings for the classification are shown in the following table:
Figure BDA0003297844610000122
Figure BDA0003297844610000131
TABLE 2 grading threshold and meaning look-up table
Specifically, the variance and the standard deviation in table 2 can be calculated according to the strength scores of different evaluation area ranges at the same industry chain node.
In some optional embodiments, the industry nodes of the industry chain include: a first level of industry nodes of the industry chain, a second level of industry nodes of the industry chain, and a third level of industry nodes of the industry chain, the method further comprising: calculating the strength score of a third-level industrial node of the industrial chain according to the weight and the score of the plurality of evaluation indexes of the industrial node of the industrial chain; calculating the strength score of the second-level industry node of the industry chain according to the strength score of the third-level industry node of the industry chain under the second-level industry node of the industry chain and the weight of the third-level industry node of the industry chain under the second-level industry node of the industry chain; and calculating the strength score of the first-level industry node of the industry chain according to the strength score of the second-level industry node of the industry chain under the first-level industry node of the industry chain and the weight of the second-level industry node of the industry chain under the first-level industry node of the industry chain. Therefore, the strength score of the second level industry node of the industry chain can be accurately calculated through the strength score of the third level industry node of the industry chain under the second level industry node of the industry chain and the weight of the third level industry node of the industry chain under the second level industry node of the industry chain. In addition, the strength score of the first-level industry node of the industry chain can be accurately calculated through the strength score of the second-level industry node of the industry chain under the first-level industry node of the industry chain and the weight of the second-level industry node of the industry chain under the first-level industry node of the industry chain.
In a specific example, the evaluation target of the strength of the industrial chain is the industrial nodes of each level of the industrial chain. For example, when the object of the industrial chain strength evaluation is each level of industrial nodes of the intelligent networked automobile industrial chain, the first level industrial nodes of the intelligent networked automobile industrial chain can be the automobile core spare and accessory production (upstream), the automobile intelligent support system (midstream) and the whole automobile manufacturing and operation maintenance (downstream), etc., the second level industrial nodes of the intelligent networked automobile industrial chain can be the automobile transmission, the automobile body, the automobile transmission system, the automobile electrical system, the automobile electronic system, the automobile running system, the automobile braking system, etc., and the third level industrial nodes of the intelligent networked automobile industrial chain can be the planetary gear, the clutch, the synchronizer, the differential, the hydraulic torque converter, the hydraulic oil pump, etc. Further, evaluation is performed from the final industrial node, and the strength score of the node of the previous layer is synthesized based on the strength score of the final industrial node. And scoring each evaluation index, then multiplying by corresponding weight, and finally weighting and summing to obtain the score of each final-stage industrial node. In actual operation, the weight setting and the score of each evaluation index have no unified standard, can be determined according to data conditions, and can be increased or decreased for partial evaluation indexes. Specifically, assuming that the industry chain is divided into three levels, and the third level has 15 nodes, the strength score CI of a node of a certain third leveliThe calculation method of (i ═ 1 … 15) adopts a linear weighting mode, namely:
Figure BDA0003297844610000141
wherein λ isnAs the weight of each evaluation index,
Figure BDA0003297844610000142
is the score value of each evaluation index. Assuming that the number of second-level nodes of the industry chain is 5, the strength score RI of the second-level nodei(i-1 … 5) is weighted by the nodes of the third level below the secondary node. Similarly, the score of the first level node is obtained by weighting the second level node under the first level node.
In a specific example, as shown in fig. 1B, second enterprise index data of the enterprises in the evaluation area range in the historical time period is extracted from a plurality of enterprise data sources, data cleaning is performed on the second enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain third enterprise index data of the enterprises in the evaluation area range in the historical time period, data fusion is performed on the third enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain first enterprise index data of the enterprises in the evaluation area range in the historical time period, the first enterprise index data of the enterprises in the evaluation area range in the historical time period is stored in the data warehouse, and then, according to a plurality of evaluation indexes for evaluating the strengths and weaknesses of the industrial nodes of the industrial chain, processing (feature engineering) first enterprise index data of enterprises in the evaluation area range in the data warehouse in a historical time period to obtain a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain, developing a model according to the evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, and performing online operation after the model is developed. Specifically, a threshold value of the plurality of evaluation indexes of an industrial node of the industrial chain is determined based on a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain, a score of the plurality of evaluation indexes of the industrial node of the industrial chain is determined based on the threshold value of the plurality of evaluation indexes of the industrial node of the industrial chain, a weight of the plurality of evaluation indexes of the industrial node of the industrial chain is determined based on a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain, and a strength score of the industrial node of the industrial chain is determined based on the weight and the score of the plurality of evaluation indexes of the industrial node of the industrial chain; and finally, determining 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.
According to the method for evaluating the strength of the industrial chain provided by the embodiment of the application, the first enterprise index data of enterprises in the evaluation area range in the data warehouse in the historical time period is processed according to the plurality of evaluation indexes for evaluating the strength of the industrial nodes of the industrial chain, so as to obtain the plurality of evaluation index data of the plurality of enterprises of the industrial nodes of the industrial chain, the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain are determined according to the plurality of evaluation index data of the plurality of enterprises of the industrial nodes of the industrial chain, the scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain are determined according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain, and the scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain can be accurately determined. In addition, the weights of the evaluation indexes of the industrial nodes of the industrial chain are determined according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, the strength score of the industrial node of the industrial chain is determined according to the weights and the scores of the evaluation indexes of the industrial nodes of the industrial chain, and the strength evaluation result of the industrial node of the industrial chain can be accurately determined according to the strength score of the industrial node of the industrial chain, so that the strength of the industrial node of the industrial chain can be effectively evaluated to reflect the strength of the industrial node of the industrial chain.
The method for evaluating the strength of the industrial chain provided by the embodiment can be executed by any suitable device with data processing capability, including but not limited to: cameras, terminals, mobile terminals, PCs, servers, in-vehicle devices, entertainment devices, advertising devices, Personal Digital Assistants (PDAs), tablet computers, notebook computers, handheld game consoles, smart glasses, smart watches, wearable devices, virtual display devices or display enhancement devices (such as Google Glass, Oculus rise, Hololens, Gear VR), and the like.
Referring to fig. 2, a schematic configuration diagram of an evaluation apparatus for evaluating the strength of an industrial chain according to a second embodiment of the present application is shown.
The evaluation device for the strength of the industrial chain provided by the embodiment comprises: the processing module 201 is configured to process, according to a plurality of evaluation indexes used for evaluating strengths and weaknesses of industrial nodes of an industrial chain, first enterprise index data of enterprises within a range of an evaluation area in a data warehouse within a historical time period, so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain; a first determining module 202, configured to determine threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain, and determine scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain; a second determining module 203, configured to determine weights of the evaluation indexes of the plurality of enterprises of the industrial node of the industrial chain according to a plurality of evaluation index data of the plurality of enterprises of the industrial node of the industrial chain, and determine a strength score of the industrial node of the industrial chain according to the weights and scores of the evaluation indexes of the industrial node of the industrial chain; a third determining module 204, configured to determine a strength evaluation result of an industry node of the industry chain according to the strength score of the industry node of the industry chain.
Optionally, before the processing module 201, the apparatus further includes: the extraction module is used for extracting second enterprise index data of enterprises in the evaluation area range in the historical time period from a plurality of enterprise data sources; the data cleaning module is used for performing data cleaning on second enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain third enterprise index data of the enterprises in the evaluation area range in the historical time period; the data fusion module is used for performing data fusion on third enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain first enterprise index data of the enterprises in the evaluation area range in the historical time period; and the storage module is used for storing the first enterprise index data of the enterprises in the evaluation area range in the historical time period into the data warehouse.
Optionally, the data cleansing module is specifically configured to: performing missing value processing on second enterprise index data of the enterprise in the evaluation area range in the historical time period by adopting a missing value completion mode; clustering the second enterprise index data subjected to the missing value processing by adopting a clustering algorithm to obtain a clustering result of the second enterprise index data subjected to the missing value processing; and according to the clustering result, identifying abnormal values in the second enterprise index data subjected to missing value processing, and removing the abnormal values to obtain third enterprise index data of enterprises in the evaluation area range in the historical time period.
Optionally, the processing module 201 is specifically configured to: screening the first enterprise index data according to the plurality of evaluation indexes to obtain the screened first enterprise index data; and determining a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain according to the screened first enterprise index data.
Optionally, the first determining module 202 is specifically configured to: determining the distribution condition of evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain; determining a threshold value of the same evaluation index of the industrial nodes of the industrial chain according to the distribution state and the preset distribution proportion of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain.
Optionally, the first determining module 202 is specifically configured to: determining the mean value and the standard deviation of evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain; and determining the threshold value of the same evaluation index of the industrial node of the industrial chain according to the mean value and the standard deviation of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial node of the industrial chain.
Optionally, the first determining module 202 is specifically configured to: determining threshold intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain; and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold value intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain.
Optionally, the second determining module 203 includes: the sampling submodule is used for sampling a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain in a layered random sampling mode; and the determining submodule is used for determining the weights of the evaluation indexes of the industrial nodes of the industrial chain according to the sampled evaluation index data of the enterprises of the industrial nodes of the industrial chain.
Optionally, the determining submodule is specifically configured to: carrying out non-dimensionalization processing on the sampled evaluation index data of the enterprises of the industrial nodes of the industrial chain by using an efficacy coefficient transformation method; performing weight transformation on a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain subjected to non-dimensionalization processing; calculating entropy values of a plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain after the proportion transformation; calculating difference coefficients of the evaluation indexes of the industrial nodes of the industrial chain according to entropy values of the evaluation indexes of the industrial nodes of the industrial chain; and normalizing the difference coefficients of the plurality of evaluation indexes of the industrial nodes of the industrial chain to obtain the weights of the plurality of evaluation indexes of the industrial nodes of the industrial chain.
Optionally, the industry nodes of the industry chain include: a first level of industry nodes of the industry chain, a second level of industry nodes of the industry chain, and a third level of industry nodes of the industry chain, the apparatus further comprising: the first calculation module is used for calculating the strength score of a third-level industrial node of the industrial chain according to the weight and the score of the evaluation indexes of the industrial nodes of the industrial chain; the second calculation module is used for calculating the strength score of the second-level industry node of the industry chain according to the strength score of the third-level industry node of the industry chain under the second-level industry node of the industry chain and the weight of the third-level industry node of the industry chain under the second-level industry node of the industry chain; and the third calculation module is used for calculating the strength score of the first-level industry node of the industry chain according to the strength score of the second-level industry node of the industry chain under the first-level industry node of the industry chain and the weight of the second-level industry node of the industry chain under the first-level industry node of the industry chain.
Optionally, the third determining module 204 is specifically configured to: grading the strength scores of the industrial nodes of the industrial chain to obtain the gear where the strength scores of the industrial nodes of the industrial chain are located; and determining the strength evaluation result of the industrial nodes of the industrial chain according to the gear of the strength score of the industrial nodes of the industrial chain.
Optionally, the plurality of evaluation indicators comprise at least one of: the scale and the operation strength of the industrial chain, the research and development innovation capability of the industrial chain, the market enterprise strength of the industrial chain and the stability of the supply chain of the industrial chain.
Optionally, the industry chain scale and business practices comprise at least one of: logarithm of the sum of the production mean and the sales mean, logarithm of the production mean, GDP specific gravity of the production value in the region, and logarithm of the registered capital sum; and/or, the industry chain development innovation capability comprises at least one of: the patent application amount average same-proportion change rate invented in last three years, the patent application number average same-proportion change rate invented in last three years, the trademark registration amount average same-proportion change rate invented in last three years, the copyright number average same-proportion change rate invented in last three years; and/or, the industry chain marketing enterprise capability comprises at least one of: the method comprises the following steps of (1) total stock book of enterprises on which the industrial chain is listed, total revenue income of enterprises on which the industrial chain is listed, total assets of enterprises on which the industrial chain is listed, net profit total of enterprises on which the industrial chain is listed, total employee number of enterprises on which the industrial chain is listed, research and development expense investment intensity of the enterprises on which the industrial chain is listed, proportion of persons on which the enterprises on which the industrial chain is listed, average receivable account turnover rate of the enterprises on which the industrial chain is listed and average payable account turnover rate of the enterprises on which the industrial chain is listed; and/or, the industry chain supply chain robustness comprises at least one of: the ratio of the number of enterprises on the upstream and downstream of the industry supply chain, and the ratio of the trading value on the upstream and downstream of the industry supply chain.
The apparatus for evaluating strength of an industrial chain provided in this embodiment is used to implement the method for evaluating strength of an industrial chain in the foregoing method embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described herein again.
Fig. 3 is a schematic structural diagram of an electronic device in a third embodiment of the present application; the electronic device may include:
one or more processors 301;
a computer-readable medium 302, which may be 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 industry chain as described in the above embodiment.
Fig. 4 is a hardware structure of an electronic device according to a fourth embodiment of the present application; as shown in fig. 4, 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;
wherein the processor 401, the communication interface 402, and the computer-readable medium 403 are in communication with each other via a communication bus 404;
alternatively, the communication interface 402 may be an interface of a communication module, such as an interface of a GSM module;
the processor 401 may be specifically configured to: processing first enterprise index data of enterprises in an evaluation area range in a data warehouse within a historical time period according to a plurality of evaluation indexes for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain; determining threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain, and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain; determining weights of the evaluation indexes of the enterprises of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determining strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain; and determining 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.
Processor 401 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The computer-readable medium 403 may be, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code configured to perform the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section, and/or installed from a removable medium. The computer program, when executed by a Central Processing Unit (CPU), performs the above-described functions defined in the method of the present application. It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access storage media (RAM), a read-only storage media (ROM), an erasable programmable read-only storage media (EPROM or flash memory), an optical fiber, a portable compact disc read-only storage media (CD-ROM), an optical storage media piece, a magnetic storage media piece, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code configured to carry out operations for the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may operate over any of a variety of networks: including a Local Area Network (LAN) or a Wide Area Network (WAN) -to the user's computer, or alternatively, to an external computer (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions configured to implement the specified logical function(s). In the above embodiments, specific precedence relationships are provided, but these precedence relationships are only exemplary, and in particular implementations, the steps may be fewer, more, or the execution order may be modified. That is, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present application may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a processing module, a first determining module, a second determining module, and a third determining module. The names of the modules do not limit the modules, for example, the processing module may be further described as a module that processes first enterprise index data of enterprises within a range of an evaluation area in a data warehouse in a historical time period according to a plurality of evaluation indexes for evaluating strengths and weaknesses of industrial nodes of an industrial chain to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain.
As another aspect, the present application further provides a computer-readable medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method for evaluating the strength of an industrial chain as described in the first embodiment.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be present separately and not assembled into the device. The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: processing first enterprise index data of enterprises in an evaluation area range in a data warehouse within a historical time period according to a plurality of evaluation indexes for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain; determining threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain, and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain; determining weights of the evaluation indexes of the enterprises of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determining strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain; and determining 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.
The expressions "first", "second", "said first" or "said 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 respective components. The above description is only configured for the purpose of distinguishing elements from other elements. For example, the first user equipment and the second user equipment represent different user equipment, although both are user equipment. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of the present disclosure.
When an element (e.g., a first element) is referred to as being "operably or communicatively coupled" or "connected" (operably or communicatively) to "another element (e.g., a second element) or" connected "to another element (e.g., a second element), it is understood that the element is directly connected to the other element or the element is indirectly connected to the other element via yet another element (e.g., a third element). In contrast, 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 (a second element), no element (e.g., a third element) is interposed therebetween.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims (10)

1. A method for evaluating the strength of an industrial chain, comprising:
processing first enterprise index data of enterprises in an evaluation area range in a data warehouse within a historical time period according to a plurality of evaluation indexes for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain;
determining threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain, and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain;
determining weights of the evaluation indexes of the enterprises of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determining strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain;
and determining 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.
2. The method according to claim 1, wherein before processing first enterprise index data of an enterprise in a data warehouse within a history time period within an evaluation area according to a plurality of evaluation indexes for evaluating strengths and weaknesses of industrial nodes of an industrial chain, the method further comprises:
extracting second enterprise index data of enterprises in the evaluation area range in the historical time period from a plurality of enterprise data sources;
performing data cleaning on second enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain third enterprise index data of the enterprises in the evaluation area range in the historical time period;
performing data fusion on the third enterprise index data of the enterprises in the evaluation area range in the historical time period to obtain first enterprise index data of the enterprises in the evaluation area range in the historical time period;
storing first enterprise index data of enterprises within the evaluation area range in the historical time period into the data warehouse.
3. The method for evaluating the strength of the industrial chain according to claim 2, wherein the step of performing data cleaning on the second enterprise index data of the enterprises in the evaluation area range in the historical time period comprises the following steps:
performing missing value processing on second enterprise index data of the enterprise in the evaluation area range in the historical time period by adopting a missing value completion mode;
clustering the second enterprise index data subjected to the missing value processing by adopting a clustering algorithm to obtain a clustering result of the second enterprise index data subjected to the missing value processing;
and according to the clustering result, identifying abnormal values in the second enterprise index data subjected to missing value processing, and removing the abnormal values to obtain third enterprise index data of enterprises in the evaluation area range in the historical time period.
4. The method for evaluating the strength of an industrial chain according to claim 1, wherein the processing of the first enterprise index data of the enterprise within the historical time period within the evaluation area range in the data warehouse according to a plurality of evaluation indexes for evaluating the strength of the industrial nodes of the industrial chain comprises:
screening the first enterprise index data according to the plurality of evaluation indexes to obtain the screened first enterprise index data;
and determining a plurality of evaluation index data of a plurality of enterprises of the industrial nodes of the industrial chain according to the screened first enterprise index data.
5. The method according to claim 1, wherein the determining the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain based on a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain includes:
determining the distribution condition of evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain;
determining a threshold value of the same evaluation index of the industrial nodes of the industrial chain according to the distribution state and the preset distribution proportion of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain.
6. The method according to claim 1, wherein the determining the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain based on a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain includes:
determining the mean value and the standard deviation of evaluation index data of the same evaluation index of a plurality of enterprises of the industrial nodes of the industrial chain;
and determining the threshold value of the same evaluation index of the industrial node of the industrial chain according to the mean value and the standard deviation of the evaluation index data of the same evaluation index of a plurality of enterprises of the industrial node of the industrial chain.
7. The method for evaluating the strength of an industrial chain according to claim 1, wherein the determining scores of the plurality of evaluation indexes of an industrial node of the industrial chain based on the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain includes:
determining threshold intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial nodes of the industrial chain;
and determining scores of the plurality of evaluation indexes of the industrial nodes of the industrial chain according to the threshold value intervals of the plurality of evaluation indexes of the industrial nodes of the industrial chain.
8. An apparatus for evaluating the strength of an industrial chain, comprising:
the processing module is used for processing first enterprise index data of enterprises in an evaluation area range in a data warehouse in a historical time period according to a plurality of evaluation indexes used for evaluating the strength of industrial nodes of an industrial chain so as to obtain a plurality of evaluation index data of the enterprises of the industrial nodes of the industrial chain;
a first determining module, configured to determine threshold values of the plurality of evaluation indexes of an industrial node of the industrial chain according to a plurality of evaluation index data of a plurality of enterprises of the industrial node of the industrial chain, and determine scores of the plurality of evaluation indexes of the industrial node of the industrial chain according to the threshold values of the plurality of evaluation indexes of the industrial node of the industrial chain;
a second determining module, configured to determine weights of the evaluation indexes of the industrial nodes of the industrial chain according to the evaluation index data of the enterprises of the industrial nodes of the industrial chain, and determine strength scores of the industrial nodes of the industrial chain according to the weights and scores of the evaluation indexes of the industrial nodes of the industrial chain;
and the third determining module is used for determining the strength evaluation result of the industrial nodes of the industrial chain according to the strength scores of the industrial nodes of the industrial chain.
9. An electronic device, characterized in that the device comprises:
one or more processors;
a computer readable medium configured to store one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method for evaluating the strength of an industry chain according to any one of claims 1 to 7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of assessing the strength of an industrial chain according to any one of claims 1 to 7.
CN202111182517.3A 2021-10-11 2021-10-11 Method, device, equipment and readable medium for evaluating strength of industrial chain Pending CN113869768A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114417020A (en) * 2022-03-29 2022-04-29 浙江省标准化研究院(金砖国家标准化(浙江)研究中心 浙江省物品编码中心) Industrial chain map construction system and method
CN114548834A (en) * 2022-04-22 2022-05-27 浙江省标准化研究院(金砖国家标准化(浙江)研究中心、浙江省物品编码中心) Standard chain analysis and construction system and method surrounding specific industry
CN116502918A (en) * 2023-05-12 2023-07-28 广东省科技基础条件平台中心 Innovative capability evaluation method of technological innovation platform

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114417020A (en) * 2022-03-29 2022-04-29 浙江省标准化研究院(金砖国家标准化(浙江)研究中心 浙江省物品编码中心) Industrial chain map construction system and method
CN114417020B (en) * 2022-03-29 2022-09-09 浙江省标准化研究院(金砖国家标准化(浙江)研究中心浙江省物品编码中心) Industrial chain map construction system and method
CN114548834A (en) * 2022-04-22 2022-05-27 浙江省标准化研究院(金砖国家标准化(浙江)研究中心、浙江省物品编码中心) Standard chain analysis and construction system and method surrounding specific industry
CN116502918A (en) * 2023-05-12 2023-07-28 广东省科技基础条件平台中心 Innovative capability evaluation method of technological innovation platform
CN116502918B (en) * 2023-05-12 2024-04-05 广东省科技基础条件平台中心 Innovative capability evaluation method of technological innovation platform

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