Novel power system industry chain scientific and technological innovation capability assessment method and system

Abstract

The invention discloses a novel electric power system industry chain scientific and technological innovation capability assessment method and a corresponding system, and the method can assess the scientific and technological innovation capability of an enterprise in a novel electric power system industry chain in a multi-dimensional manner, covers key fields of technology research and development, project driving, market expansion and the like, and is high in practicability. Comprising digital improvement and external resource integration capability, and comprehensiveness and accuracy of an evaluation result are ensured. A method based on a knowledge graph is utilized to effectively identify a'neck 'key technology and a core product in a supply chain. The identification method helps an enterprise to timely discover and deal with potential risks in supply chain management, and ensures stable development of an industrial chain. Through collection and processing of enterprise related information, a supply chain digital panorama based on Neo4j is constructed. The map not only can visually display the position of an enterprise in an industrial chain, but also can provide decision support to help the enterprise better manage and optimize a supply chain.

Description

Technical Field

[0001] The present invention relates to the field of dynamic uncertainty measurement technology, and in particular to a method and system for evaluating the technological innovation capability of a new power system industry chain. Background Art

[0002] With the rapid development of new power systems, the power industry is facing unprecedented technological changes and challenges. Scientific and technological innovation capabilities have become a key factor for enterprises to stand out in fierce competition. However, there are several major problems with traditional scientific and technological innovation capability evaluation methods: ① Lack of systematicity and comprehensiveness: Existing evaluation methods are mostly limited to a single dimension or a specific field, and it is difficult to cover the overall scientific and technological innovation capabilities of enterprises. These methods usually ignore the diverse factors in the innovation process, such as R&D organization management, market competitiveness and digital transformation capabilities, resulting in one-sided evaluation results. ② Insufficient dynamics: Most existing evaluation methods are based on static data and cannot reflect the innovation capabilities of enterprises in a rapidly changing market environment in real time. This lack of dynamics makes the evaluation results lag behind and cannot effectively guide the adjustment of enterprises' innovation strategies. ③ Weak identification of key supply chain technologies: In supply chain management, existing technical evaluation methods are difficult to accurately identify "stuck neck" key technologies and core products. This not only affects the stability and security of the supply chain, but also restricts the initiative of enterprises in technological research. ④ Lack of digital support: With the acceleration of the digital transformation of the industrial chain, traditional evaluation methods cannot make full use of digital tools such as big data and knowledge graphs, resulting in inefficient evaluation processes and low information utilization. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a new method for evaluating the scientific and technological innovation capability of the power system industry chain, which can systematically, comprehensively and dynamically evaluate the innovation capability of enterprises, and build a panoramic map of the supply chain through digital tools to help enterprises identify and enhance their core competitiveness.

[0004] The present invention also proposes a system having the above-mentioned new power system industry chain scientific and technological innovation capability evaluation method.

[0005] The method for evaluating the technological innovation capability of the new power system industry chain according to the first aspect of the present invention is characterized by comprising the following steps:

[0006] Obtain relevant information about enterprises in the power system industry chain, and build corresponding primary, secondary and tertiary evaluation indicator systems based on relevant innovation evaluation standards;

[0007] Determine the weights of the first-level, second-level and third-level evaluation indicators, and calculate the innovation capability of the enterprise based on the weights of the indicators;

[0008] Based on the relevant information of enterprises and the calculated innovation capabilities of enterprises, a knowledge graph between enterprises is constructed using the Neo4j graph database, and a digital panoramic graph of the supply chain is constructed based on the knowledge graph;

[0009] Based on the digital panoramic map of the supply chain, a comprehensive assessment of the company's innovation capabilities is conducted.

[0010] The method for evaluating the technological innovation capability of the new power system industrial chain according to the embodiment of the present invention has at least the following beneficial effects: by constructing a systematic and comprehensive evaluation index system, it is possible to evaluate the technological innovation capability of enterprises in the new power system industrial chain in multiple dimensions, covering key areas such as technology research and development, project drive, and market expansion, including digital enhancement and external resource integration capabilities, to ensure the comprehensiveness and accuracy of the evaluation results. Using a knowledge graph-based method, the "bottleneck" key technologies and core products in the supply chain are effectively identified. This identification method helps enterprises to promptly discover and respond to potential risks in supply chain management and ensure the stable development of the industrial chain. By collecting and processing relevant information about the enterprise, a digital panoramic map of the supply chain based on Neo4j is constructed. This map can not only intuitively display the position of the enterprise in the industrial chain, but also provide decision support to help enterprises better manage and optimize the supply chain.

[0011] According to some embodiments of the present invention, the relevant information of the enterprise includes data on technology research and development, market expansion, digitalization level, and external resource integration.

[0012] According to some embodiments of the present invention, the process of determining the weights of the primary, secondary and tertiary evaluation indicators includes:

[0013] Set up plan U i (i=1, 2, ..., n) under a certain criterion P i The judgment matrix A is:

[0014]

[0015] The elements of the judgment matrix A are normalized by column, where a ij is the index of the jth feature of the i-th solution:

[0016]

[0017] Add row by row, where a ij is the index of the jth feature of the i-th solution:

[0018]

[0019] Normalize W:

[0020]

[0021] According to some embodiments of the present invention, in the step of using the Neo4j graph database to construct a knowledge graph between enterprises based on the relevant information of the enterprises and the calculated enterprise innovation capabilities, a multi-criteria coordinated sorting method is used to select a supplier selection decision that is closest to the best supplier, specifically including:

[0022] Use aggregate functions for comprehensive evaluation:

[0023]

[0024] Where 1≤p≤∞, j=1,2,...,m, m is the number of alternatives, y ij For alternative Y i The i-th index, L pj For plan Y i The distance from the ideal solution;

[0025] Determine the solution set Y = {Y i , Y2, ..., Y m} and attribute set G = {G1, G2, ..., G n}, construct the decision matrix F = (f ij ) m×n , where f ij Represents the j-th indicator attribute of the i-th solution;

[0026] The decision matrix is ​​normalized using 0-1 transformation. j The attribute is a benefit-type indicator, and the normalized decision matrix F′=(f′ ij ) m×n :

[0027]

[0028] Determine the positive ideal solution f from the normalized matrix + and negative ideal solution f -

[0029]

[0030] Among them, f j + =max i (f′ ij ), f j - =min i (f′ ij )

[0031] Calculate each alternative Y i ∈Y group benefit value Si 、Individual regret value R i and the compromise value Q i

[0032]

[0033]

[0034]

[0035] Among them, S i is the maximum group utility, which is L 1，j Measure; R i Taking the small individual regret is L ∞，j Measure; ω j is the attribute weight; S + =min i (S i ), S - =max i (S i ), R + =min i (R i ), R - =max i (R i );v is the decision-making mechanism coefficient, v∈[0,1]. When v>0.5, the decision is made according to the decision-making mechanism of maximum group utility; when v=0.5, the decision is made according to the decision-making mechanism in which the decision makers reach a consensus through consultation; when v<0.5, the decision is made according to the decision-making mechanism of minimum regret;

[0036] Press S i , R i and Q i The alternative plans are sorted by value, the smaller the data, the better the plan;

[0037] Identify compromise solutions.

[0038] According to some embodiments of the present invention, determining a compromise solution specifically includes:

[0039] Press Q i The sorting by increasing value is Y (1) , Y (2) , ..., Y (J) , ..., Y (m) , then the ranking of the alternatives can be determined based on the first ranking condition and the second ranking condition:

[0040] First sorting condition: Acceptable advantage condition:

[0041]

[0042] Second sorting condition: Acceptable stability condition of the decision-making process: Option Y (1) Must also be in accordance with S i Value or R i The value-first scheme.

[0043] According to some embodiments of the present invention, based on the relevant information of the enterprise and the calculated enterprise innovation capability, a knowledge graph between enterprises is constructed using a Neo4j graph database, and a digital panoramic graph of the supply chain is constructed based on the knowledge graph, specifically including:

[0044] Collect and organize data from companies in the power system industry chain, and ensure the accuracy and consistency of the data used through data cleaning and classification;

[0045] Using graph database technologies such as Neo4j, the sorted enterprise data is converted into a knowledge graph; the knowledge graph includes the relationships between enterprises, such as technical cooperation relationships and supply chain dependencies;

[0046] Based on the knowledge graph, a digital panoramic map of the supply chain is further drawn, which includes information on the relationships, technical nodes and core products of various enterprises in the industrial chain.

[0047] The new power system industry chain scientific and technological innovation capability evaluation system according to the second aspect of the present invention is characterized by comprising:

[0048] The evaluation index construction module can obtain relevant information of enterprises in the power system industry chain and construct corresponding primary, secondary and tertiary evaluation index systems according to relevant standards for innovation evaluation;

[0049] An indicator weight determination module, capable of determining the weights of the first-level, second-level and third-level evaluation indicators, and calculating the innovation capability of the enterprise according to the indicator weights;

[0050] The supplier solution selection module can use the Neo4j graph database to build a knowledge graph between enterprises based on the relevant information of the enterprise and the calculated enterprise innovation capabilities, and build a digital panoramic map of the supply chain based on the knowledge graph;

[0051] The comprehensive evaluation module can comprehensively evaluate the innovation capability of an enterprise based on the digital panoramic map of the supply chain.

[0052] According to some embodiments of the present invention, the relevant information of the enterprise includes data on technology research and development, market expansion, digitalization level, and external resource integration.

[0053] According to some embodiments of the present invention, the process of determining the weights of the primary, secondary and tertiary evaluation indicators includes:

[0054] Set up plan U i (i=1, 2, ..., n) under a certain criterion P i The judgment matrix A is:

[0055]

[0056] The elements of the judgment matrix A are normalized by column, where a ij is the index of the jth feature of the i-th solution:

[0057]

[0058] Add row by row, where W is the weight vector, w i is the weight of each option:

[0059]

[0060] Normalize W:

[0061]

[0062] According to some embodiments of the present invention, in the supplier solution selection module, a multi-criteria coordinated sorting method is used to select a supplier selection decision that is closest to the best supplier, specifically including:

[0063] Use aggregate functions for comprehensive evaluation:

[0064]

[0065] Where 1≤p≤∞, j=1,2,...,m, m is the number of alternatives, y ij For alternative Y i The i-th index, L pj For plan Y i The distance from the ideal solution;

[0066] Determine the solution set Y = {Y i , Y2, ..., Y m} and attribute set G = {G1, G2, ..., G n}, construct the decision matrix F = (f ij ) m×n ;

[0067] The decision matrix is ​​normalized using 0-1 transformation. j The attribute is a benefit-type indicator, and the normalized decision matrix F′=(f′ ij ) m×n :

[0068]

[0069] Determine the positive ideal solution f from the normalized matrix + and negative ideal solution f -

[0070]

[0071]

[0072] Among them, f j + =max i (f′ ij ), f j - =min i (f′ ij )

[0073] Calculate each alternative Y i ∈Y group benefit value S i 、Individual regret value R i and the compromise value Q i

[0074]

[0075]

[0076]

[0077] Among them, S i is the maximum group utility, which is L 1，j Measure; R i Taking the small individual regret is L ∞，j Measure; ω j is the attribute weight; S + =min i (S i ), S - =max i (S i ), R + =min i (R i ), R - =max i (R i );v is the decision-making mechanism coefficient, v∈[0,1]. When v>0.5, the decision is made according to the decision-making mechanism of maximum group utility; when v=0.5, the decision is made according to the decision-making mechanism in which the decision makers reach a consensus through consultation; when v<0.5, the decision is made according to the decision-making mechanism of minimum regret;

[0078] Press S i , R i and Qi The alternative plans are sorted by value, the smaller the data, the better the plan;

[0079] Identify compromise solutions.

[0080] According to some embodiments of the present invention, determining a compromise solution specifically includes:

[0081] Press Q i The sorting by increasing value is Y (1) , Y (2) , ..., Y (J) , ..., Y (m) , then the ranking of the alternatives can be determined based on the first ranking condition and the second ranking condition:

[0082] First sorting condition: Acceptable advantage condition:

[0083]

[0084] Second sorting condition: Acceptable stability condition of the decision-making process: Option Y (1) Must also be in accordance with S i Value or R i The value-first scheme.

[0085] According to some embodiments of the present invention, the supplier solution selection module specifically includes:

[0086] Collect and organize data from companies in the power system industry chain, and ensure the accuracy and consistency of the data used through data cleaning and classification;

[0087] Using graph database technologies such as Neo4j, the sorted enterprise data is converted into a knowledge graph; the knowledge graph includes the relationships between enterprises, such as technical cooperation relationships and supply chain dependencies;

[0088] Based on the knowledge graph, a digital panoramic map of the supply chain is further drawn, which includes information on the relationships, technical nodes and core products of various enterprises in the industrial chain.

[0089] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0091] Figure 1 A schematic diagram of the steps of a method for evaluating the technological innovation capability of a new power system industry chain according to an embodiment of the present invention;

[0092] Figure 2 for Figure 1 A schematic diagram of the knowledge graph of the mid-to-high-end power transmission and transformation equipment industry chain of the new power system industry chain technological innovation capability evaluation method is shown;

[0093] Figure 3 for Figure 2 A schematic diagram showing the corresponding query function of the knowledge graph of the mid-to-high-end power transmission and transformation equipment industry chain;

[0094] Figure 4 A structural block diagram of a new power system industry chain scientific and technological innovation capability assessment system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0095] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0096] In the description of the present invention, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., and orientations or positional relationships indicated are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0097] In the description of the present invention, "several" means one or more, "more" means more than two, "greater than", "less than", "exceed" etc. are understood as not including the number itself, and "above", "below", "within" etc. are understood as including the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0098] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0099] like Figure 1 As shown, an embodiment of the present invention provides a new method for evaluating the technological innovation capability of the power system industry chain, which at least includes the following steps:

[0100] Step S100: Obtain relevant information of enterprises in the power system industry chain, and construct corresponding primary, secondary and tertiary evaluation indicator systems according to relevant standards for innovation evaluation.

[0101] First, collect relevant information about enterprises in the power system industry chain, including data on technology research and development, market expansion, digitalization level, external resource integration, etc. According to the relevant standards for innovation evaluation, construct corresponding first-level, second-level and third-level evaluation indicator systems. For details, refer to Table 1:

[0102] Table 1 Innovation evaluation index system

[0103]

[0104]

[0105] Step S200: Determine the weights of the first-level, second-level and third-level evaluation indicators, and calculate the innovation capability of the enterprise according to the indicator weights.

[0106] This embodiment uses the summation method to solve the weight. Assume that each solution U i (i=1,2,…,n) in a certain criterion P i The judgment matrix is ​​as follows:

[0107]

[0108] (1) Normalize the elements in A by column, where a ij is the index of the jth feature of the i-th solution:

[0109]

[0110] (2) Add row by row, where W is the weight vector, w i is the weight of each option:

[0111]

[0112] (3) Normalize W:

[0113]

[0114] The scale determination method is shown in Table 2.

[0115] Table 2 Judgment scale method

[0116]

[0117] Step S300: Based on the relevant information of the enterprise and the calculated enterprise innovation capability, a knowledge graph between enterprises is constructed using the Neo4j graph database, and a digital panoramic graph of the supply chain is constructed based on the knowledge graph.

[0118] The multi-criteria coordinated ranking method (VIKOR, VIseKriterijumska Optimizacija I Kompromisno Resenje) is used to select the supplier selection decision that is closest to the best supplier based on multiple indicators.

[0119] VIKOR uses aggregate functions for comprehensive evaluation:

[0120]

[0121] Where 1≤p≤∞, j=1,2,...,m, m is the number of alternatives, y ij For alternative Y i The i-th index, L pj For plan Y i The distance from the ideal solution.

[0122] Suppose the problem under consideration has m solutions Y i (i=1,2,...,m), the solution set Y={Y i , Y2, ..., Y m}, the index for evaluating each solution is G j (j=1,2,...,n), then the attribute set is G={G1,G2,...,G n}, indicator G j The weight of is known and can be obtained by summation method. Assume that f ij Indicates plan Y i ∈Y in attribute G i ∈G, the matrix F=(f ij ) m×n is the decision matrix of the multi-attribute decision-making problem, and the decision steps are as follows:

[0123] Step S301: Determine the solution set Y = {Y i , Y2, ..., Y m} and attribute set G = {G1, G2, ..., G n}, construct the decision matrix F = (f ij ) m×n

[0124] Step S302: normalize the decision matrix using 0-1 transformation. j The attribute is a benefit-type indicator, and the normalized decision matrix F′=(f′ ij )m×n :

[0125]

[0126] Step S303: Determine the positive ideal solution f according to the normalized matrix + and negative ideal solution f -

[0127]

[0128]

[0129] Among them, f j + =max i (f′ ij ), f j - =min i (f′ ij )

[0130] Step S304: Calculate each alternative solution Y i ∈Y group benefit value S i 、Individual regret value R i and the compromise value Q i

[0131]

[0132]

[0133] Among them, S i is the maximum group utility, which is L 1，j Measure; R i Taking the small individual regret is L ∞，j Measure; ω j is the attribute weight; S + =min i (S i ), S - =max i (S i ), R + =min i (R i ), R - =max i (R i );v is the decision mechanism coefficient, v∈[0,1]. When v>0.5, the decision is made according to the decision mechanism of maximum group utility; when v=0.5, the decision is made according to the decision mechanism in which the decision makers reach a consensus through consultation; when v<0.5, the decision is made according to the decision mechanism of minimum regret.

[0134] Step S305: Sort the solutions. i , R i and Q i The smaller the value, the better the solution.

[0135] Step S306: Determine the compromise solution. Press Q i The sorting by increasing value is Y (1) , Y (2) , ..., Y (J) , ..., Y (m) , then the ranking of alternatives can be determined based on ranking conditions 1 and 2:

[0136] Sorting condition 1 Acceptable advantage conditions:

[0137]

[0138] Sorting condition 2 Acceptable stability condition of decision process: Option Y (1) Must also be in accordance with S i Value or R i The value-first scheme.

[0139] If sorting conditions 1 and 2 are met at the same time, then Y (1) is the optimal solution. When only sorting condition 1 is met but not sorting condition 2, solution Y (1) and Y (2) All are compromise solutions; if 2 is satisfied but 1 is not, then pass

[0140]

[0141] Get the maximum J, then plan Y (1) , Y (2) , ..., Y (J) A compromise solution.

[0142] Step S400: Comprehensively evaluate the innovation capability of the enterprise based on the digital panoramic map of the supply chain.

[0143] Collect and organize data of enterprises related to the power system industry chain, including production capacity, technology patents, market cooperation, logistics information, etc. Ensure the accuracy and consistency of the data used through data cleaning and classification.

[0144] Using graph database technologies such as Neo4j, the sorted enterprise data is converted into a knowledge graph. The graph shows the connections between enterprises, such as technical cooperation relationships, supply chain dependencies, etc. Based on the knowledge graph, a digital panoramic map of the supply chain is further drawn. The map shows the relationships, technical nodes, and core products of each enterprise in the industrial chain. This map not only helps enterprises intuitively understand their position in the industrial chain, but also provides tools for analyzing supply chain risks and optimizing management.

[0145] like Figure 2 As shown, the knowledge graph of the high-end power transmission and transformation equipment industry chain is displayed. Through the graph, we can clearly see the roles of each company in the industry chain and their relationships with each other. Key companies and their affiliated companies are connected through various relationships (such as supply relationships, etc.) to form a complex network. These relationships show the supply and demand relationships, partnerships and competition relationships in each link of the industry chain. The number in the upper right corner of each company indicates the recommended ranking of suppliers of similar products. The higher the ranking, the higher the overall score. The relationship between different companies is marked with arrows in the graph, showing the entire process from raw material supply to product production to final application. You can view suppliers that provide corresponding products through the product search bar in the upper left corner, such as Figure 3 shown.

[0146] Through the product search bar, you can see the supplier of the product and its upstream suppliers. At the same time, for each upstream supplier's past bidding records, a comprehensive evaluation is conducted, and its scores in the past five to ten years are displayed in the blue box on the right. The triangle above the blue box shows the supplier's advantages and disadvantages in different indicators. Click on different upstream supplier icons to see the specific scores and advantages and disadvantages of different suppliers. This allows companies to intuitively see the comparison between different suppliers and recommend the most suitable upstream supplier for the corresponding product.

[0147] Another embodiment of the present application provides a novel power system industry chain technological innovation capability evaluation system 20, such as Figure 4 As shown, including:

[0148] The evaluation index construction module 201 can obtain relevant information of enterprises in the power system industry chain and construct corresponding primary, secondary and tertiary evaluation index systems according to relevant standards for innovation evaluation;

[0149] The indicator weight determination module 202 is capable of determining the weights of the first-level, second-level and third-level evaluation indicators, and calculating the innovation capability of the enterprise according to the indicator weights;

[0150] The supplier solution selection module 203 can construct a knowledge graph between enterprises using the Neo4j graph database based on the relevant information of the enterprises and the calculated innovation capabilities of the enterprises, and construct a digital panoramic graph of the supply chain based on the knowledge graph;

[0151] The comprehensive evaluation module 204 can comprehensively evaluate the innovation capability of the enterprise based on the digital panoramic map of the supply chain.

[0152] The device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0153] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0154] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the above-mentioned implementation mode. Technical personnel familiar with the field can also make various equivalent deformations or substitutions without violating the spirit of the present application. These equivalent deformations or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A new method for evaluating the scientific and technological innovation capability of the power system industry chain, characterized in that: The following steps are involved: Obtain relevant information about enterprises in the power system industry chain, and build corresponding primary, secondary and tertiary evaluation indicator systems based on relevant innovation evaluation standards; Determine the weights of the first-level, second-level and third-level evaluation indicators, and calculate the innovation capability of the enterprise based on the weights of the indicators; Based on the relevant information of enterprises and the calculated innovation capabilities of enterprises, a knowledge graph between enterprises is constructed using the Neo4j graph database, and a digital panoramic graph of the supply chain is constructed based on the knowledge graph; Based on the digital panoramic map of the supply chain, a comprehensive assessment of the company's innovation capabilities is conducted.

2. The method according to claim 1, characterized in that The relevant information of the enterprise includes data on technology research and development, market expansion, digitalization level, and external resource integration.

3. The method according to claim 1, characterized in that The process of determining the weights of the first-level, second-level and third-level evaluation indicators includes: Set up plan U i (i=1,2,…,n) in a certain criterion P i The judgment matrix A is: The elements of the judgment matrix A are normalized by column, where a ij is the index of the jth feature of the i-th solution: Add row by row, where W is the weight vector, w i is the weight of each option: Normalize W:

4. The method according to claim 1, characterized in that: In the step of using Neo4j graph database to construct the knowledge graph between enterprises based on the relevant information of the enterprises and the calculated enterprise innovation capabilities, a multi-criteria coordinated sorting method is used to select the supplier selection decision that is closest to the best supplier, specifically including: Use aggregate functions for comprehensive evaluation: Among them, 1≤p≤∞,j=1,2,…,m, m is the number of alternatives, y ij For alternative Y i The i-th index, L pj For plan Y i The distance from the ideal solution; Determine the solution set Y = {Y1, Y2, ..., Y m } and attribute set G = {G1, G2, …, G n }, construct the decision matrix F = (f ij ) m×n , where f ij Represents the j-th indicator attribute of the i-th solution; The decision matrix is ​​normalized using 0-1 transformation. j The attribute is a benefit-type indicator, and the normalized decision matrix F′=(f′ ij ) m×n : Determine the positive ideal solution f from the normalized matrix + and negative ideal solution f - in, Calculate each alternative Y i ∈Y group benefit value S i 、Individual regret value R i and the compromise value Q i Among them, S i is the maximum group utility, which is L 1,j Measure; R i Taking the small individual regret is L ∞,j Measure; ω j is the attribute weight; S + =min i (S i ),S - =max i (S i ),R + =min i (R i ),R - =max i (R i );v is the decision-making mechanism coefficient, v∈[0,1]. When v>0.5, the decision is made according to the decision-making mechanism of maximum group utility; when v=0.5, the decision is made according to the decision-making mechanism in which the decision makers reach a consensus through consultation; when v<0.5, the decision is made according to the decision-making mechanism of minimum regret; Press S i , R i and Q i The alternative plans are sorted by value, the smaller the data, the better the plan; Identify compromise solutions.

5. The method according to claim 4, characterized in that The determination of the compromise solution specifically includes: Press Q o The sorting by increasing value is Y (1) ,Y (2) ,…,Y (J) ,…,Y (m) , then the ranking of the alternatives can be determined based on the first ranking condition and the second ranking condition: First sorting condition: Acceptable advantage condition: Second sorting condition: Acceptable stability condition of the decision-making process: Option Y (1) Must also be in accordance with S i Value or R i The value-first scheme.

6. The method according to claim 1, characterized in that Based on the relevant information of enterprises and the calculated innovation capabilities of enterprises, the Neo4j graph database is used to build a knowledge graph between enterprises, and a digital panoramic graph of the supply chain is built based on the knowledge graph, including: Collect and organize data from companies in the power system industry chain, and ensure the accuracy and consistency of the data used through data cleaning and classification; Using graph database technologies such as Neo4j, the sorted enterprise data is converted into a knowledge graph; the knowledge graph includes the relationships between enterprises, such as technical cooperation relationships and supply chain dependencies; Based on the knowledge graph, a digital panoramic map of the supply chain is further drawn, which includes information on the relationships, technical nodes and core products of various enterprises in the industrial chain.

7. A new type of power system industry chain scientific and technological innovation capability evaluation system, characterized by: include: The evaluation index construction module can obtain relevant information of enterprises in the power system industry chain and construct corresponding primary, secondary and tertiary evaluation index systems according to relevant standards for innovation evaluation; An indicator weight determination module, capable of determining the weights of the first-level, second-level and third-level evaluation indicators, and calculating the innovation capability of the enterprise according to the indicator weights; The supplier solution selection module can use the Neo4j graph database to build a knowledge graph between enterprises based on the relevant information of the enterprise and the calculated enterprise innovation capabilities, and build a digital panoramic map of the supply chain based on the knowledge graph; The comprehensive evaluation module can comprehensively evaluate the innovation capability of an enterprise based on the digital panoramic map of the supply chain.

8. The system according to claim 7, characterized in that The relevant information of the enterprise includes data on technology research and development, market expansion, digitalization level, and external resource integration.

9. The system according to claim 7, characterized in that The process of determining the weights of the first-level, second-level and third-level evaluation indicators includes: Set up plan U i (i=1,2,…,n) in a certain criterion P i The judgment matrix A is: The elements of the judgment matrix A are normalized by column, where a ij is the index of the jth feature of the i-th solution: Add row by row, where W is the weight vector, w i is the weight of each option: Normalize W:

10. The system according to claim 7, characterized in that In the supplier selection module, a multi-criteria coordinated ranking method is used to select the supplier selection decision that is closest to the best supplier, specifically including: Use aggregate functions for comprehensive evaluation: Among them, 1≤p≤∞,j=1,2,…,m, m is the number of alternatives, y ij For alternative Y i The i-th index, L pj For plan Y i The distance from the ideal solution; Determine the solution set Y = {Y1, Y2, ..., Y m } and attribute set G = {G1, G2, …, G n }, construct the decision matrix F = (f ij ) m×n ; The decision matrix is ​​normalized using 0-1 transformation. j The attribute is a benefit-type indicator, and the normalized decision matrix F′=(f′ ij ) m×n , where f ij Represents the j-th indicator attribute of the i-th solution: Determine the positive ideal solution f from the normalized matrix + and negative ideal solution f - in, Calculate each alternative Y i ∈Y group benefit value S i 、Individual regret value R i and the compromise value Q i Among them, S i is the maximum group utility, which is L 1,j Measure; R i Taking the small individual regret is L ∞,j Measure; ω j is the attribute weight; S + =min i (S i ),S - =max i (S i ),R + =min i (R i ),R - =max i (R i );v is the decision-making mechanism coefficient, v∈[0,1]. When v>0.5, the decision is made according to the decision-making mechanism of maximum group utility; when v=0.5, the decision is made according to the decision-making mechanism in which the decision makers reach a consensus through consultation; when v<0.5, the decision is made according to the decision-making mechanism of minimum regret; Press S i , R i and Q i The alternative plans are sorted by value, the smaller the data, the better the plan; Identify compromise solutions.

11. The system according to claim 10, characterized in that The determination of the compromise solution specifically includes: Press Q i The sorting by increasing value is Y (1) ,Y (2) ,…,Y (J) ,…,Y (m) , then the ranking of the alternatives can be determined based on the first ranking condition and the second ranking condition: First sorting condition: Acceptable advantage condition: Second sorting condition: Acceptable stability condition of the decision-making process: Option Y (1) Must also be in accordance with S i Value or R i The value-first scheme.

12. The system according to claim 7, characterized in that The supplier solution selection module specifically includes: Collect and organize data from companies in the power system industry chain, and ensure the accuracy and consistency of the data used through data cleaning and classification; Using graph database technologies such as Neo4j, the sorted enterprise data is converted into a knowledge graph; the knowledge graph includes the relationships between enterprises, such as technical cooperation relationships and supply chain dependencies; Based on the knowledge graph, a digital panoramic map of the supply chain is further drawn, which includes information on the relationships, technical nodes and core products of various enterprises in the industrial chain.

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