Industrial product supply account detection method and device for industrial products in power industry, computer equipment, readable storage medium and program product

Abstract

The invention relates to an industrial product supply account detection method and device for industrial products in the power industry, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of information processing, and can improve the detection accuracy of supply accounts. The method comprises the following steps: acquiring industrial product supply characteristics of industrial products in the power industry, and determining a plurality of detection dimensions for detecting industrial product supply accounts of the industrial products in the power industry based on the industrial product supply characteristics; the industrial product supply feature indicates a supply environment in which the industrial product supply account supplies industrial products in the power industry; determining a detection dimension weight corresponding to each detection dimension according to the industry characteristics of the power industry; obtaining respective detection rules of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions; and determining a detection result of each industrial product supply account according to the detection data, the detection dimension weight and the detection rule.

Description

Technical Field

[0001] The present application relates to the field of information processing technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for detecting industrial product supply accounts for industrial products in the power industry. Background Art

[0002] In the supply chain of industrial products in the power industry, the detection system for industrial product supply accounts mostly relies on manual experience, and the evaluation of these supply accounts focuses on single indicators and subjective considerations, resulting in low detection accuracy of supply accounts. Summary of the Invention

[0003] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for industrial product supply account detection of industrial products in the power industry to address the above technical problems.

[0004] In a first aspect, the present application provides a method for detecting industrial product supply accounts for industrial products in the power industry, comprising:

[0005] Acquiring industrial product supply characteristics of an industrial product in the power industry, and determining multiple detection dimensions for detecting an industrial product supply account for the industrial product in the power industry based on the industrial product supply characteristics; the industrial product supply characteristics indicate a supply environment in which the industrial product supply account supplies the industrial product in the power industry;

[0006] Determine the detection dimension weights corresponding to each of the detection dimensions according to the industry characteristics of the power industry;

[0007] Obtaining detection rules for each of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions;

[0008] The detection results of each of the industrial product supply accounts are determined based on the detection data, the detection dimension weights and the detection rules.

[0009] In one embodiment, after obtaining the detection rules for each of the plurality of detection dimensions and the detection data of the industrial product supply account under the plurality of detection dimensions, the method further includes:

[0010] Determining, based on the industry characteristics of the power industry, the contribution of each detection indicator under the detection dimension to the detection dimension;

[0011] Based on the detection dimension weight and the contribution, weights are assigned to the detection indicators to obtain detection indicator weights corresponding to the detection indicators;

[0012] Determining the detection results of each of the industrial product supply accounts based on the detection data, the detection dimension weights, and the detection rules includes:

[0013] The detection result of the detection dimension of the industrial product supply account is determined based on the detection indicator weight, the detection data and the detection rules.

[0014] In one embodiment, the detection dimension includes an ecological construction dimension that reflects the degree of impact of the industrial product supply account on the supply environment; the detection result of each industrial product supply account is determined based on the detection data, the detection dimension weight and the detection rule, including:

[0015] The attractiveness of the industrial product supply account to other accounts in the supply environment is determined as a detection indicator under the ecological construction dimension; the other accounts are accounts associated with the industrial product supply account in the supply chain of the power industry industrial products;

[0016] In the detection data, determining the number of user registrations corresponding to the detection indicator and a preset attraction coefficient;

[0017] Calculation is performed based on the number of user registrations, the attractiveness coefficient, and the detection rules of the ecological construction dimension to determine the detection results of the ecological construction dimension of each of the industrial product supply accounts.

[0018] In one embodiment, the detection dimension includes an order processing efficiency dimension; and determining the detection result of each industrial product supply account based on the detection data, the detection dimension weights, and the detection rules includes:

[0019] Determining the processing speed of at least one key link in the order processing process of the industrial product supply account as a detection indicator under the order processing efficiency dimension;

[0020] In the detection data, time data and the detection indicator weight assigned by the detection dimension weight are determined; the time data is used to indicate the processing speed of the key link in the order processing process;

[0021] Based on the time data, the detection indicator weights and the detection rules of the order processing efficiency dimension, the detection results of the order processing efficiency of each of the industrial product supply accounts are determined.

[0022] In one embodiment, after determining the detection result of each of the industrial product supply accounts based on the detection data, the detection dimension weights, and the detection rules, the method further includes:

[0023] Ranking the industrial product supply accounts according to the detection results to obtain a ranking result;

[0024] According to the ranking results, the industrial product supply accounts are graded to obtain the detection grades corresponding to the industrial product supply accounts, and the detection grades and the detection results are displayed.

[0025] In one embodiment, displaying the detection level and the detection result further includes:

[0026] Update the displayed test results and test levels according to a preset update time to obtain updated test results and test levels of the industrial product supply account;

[0027] If the updated detection result and / or the detection level of the industrial product supply account meets the preset incentive standard, incentive prompt information is generated, and the incentive prompt information includes incentive measures for the industrial product supply account.

[0028] In a second aspect, the present application further provides an industrial product supply account detection device for industrial products in the power industry, comprising:

[0029] A supply feature identification module is configured to obtain industrial product supply features of power industry industrial products and, based on the industrial product supply features, determine multiple detection dimensions for detecting the industrial product supply account of the power industry industrial products; the industrial product supply features indicate the supply environment in which the industrial product supply account supplies the power industry industrial products;

[0030] A detection dimension construction module is used to determine the detection dimension weight corresponding to each detection dimension according to the industry characteristics of the power industry;

[0031] A detection data collection and rule configuration module, configured to obtain detection rules for each of the plurality of detection dimensions, and detection data of the industrial product supply account under the plurality of detection dimensions;

[0032] The supply account detection result determination module is used to determine the detection results of each industrial product supply account based on the detection data, the detection dimension weights and the detection rules.

[0033] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] Acquiring industrial product supply characteristics of an industrial product in the power industry, and determining multiple detection dimensions for detecting an industrial product supply account for the industrial product in the power industry based on the industrial product supply characteristics; the industrial product supply characteristics indicate a supply environment in which the industrial product supply account supplies the industrial product in the power industry;

[0035] Determine the detection dimension weights corresponding to each of the detection dimensions according to the industry characteristics of the power industry;

[0036] Obtaining detection rules for each of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions;

[0037] The detection results of each of the industrial product supply accounts are determined based on the detection data, the detection dimension weights and the detection rules.

[0038] In a fourth aspect, the present application further provides a computer-readable storage medium storing information on which a computer obtains industrial product supply characteristics of an industrial product in the power industry, and determines, based on the industrial product supply characteristics, multiple detection dimensions for detecting an industrial product supply account for the industrial product in the power industry; the industrial product supply characteristics indicate a supply environment in which the industrial product supply account supplies the industrial product in the power industry;

[0039] Determine the detection dimension weights corresponding to each of the detection dimensions according to the industry characteristics of the power industry;

[0040] Obtaining detection rules for each of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions;

[0041] The detection results of each of the industrial product supply accounts are determined based on the detection data, the detection dimension weights and the detection rules.

[0042] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0043] Acquiring industrial product supply characteristics of an industrial product in the power industry, and determining multiple detection dimensions for detecting an industrial product supply account for the industrial product in the power industry based on the industrial product supply characteristics; the industrial product supply characteristics indicate a supply environment in which the industrial product supply account supplies the industrial product in the power industry;

[0044] Determine the detection dimension weights corresponding to each of the detection dimensions according to the industry characteristics of the power industry;

[0045] Obtaining detection rules for each of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions;

[0046] The detection results of each of the industrial product supply accounts are determined based on the detection data, the detection dimension weights and the detection rules.

[0047] The above-mentioned detection method, device, computer equipment, computer-readable storage medium and computer program product for industrial product supply accounts of industrial products in the power industry obtain the industrial product supply characteristics of industrial products in the power industry, and determine multiple detection dimensions for detecting industrial product supply accounts of industrial products in the power industry based on the industrial product supply characteristics; the industrial product supply characteristics indicate the supply environment of industrial product supply accounts supplying industrial products in the power industry; according to the industry characteristics of the power industry, determine the detection dimension weights corresponding to each detection dimension; obtain the detection rules of each of the multiple detection dimensions, and the detection data of the industrial product supply accounts under the multiple detection dimensions; according to the detection data, the detection dimension weights and the detection rules, determine the detection results of each industrial product supply account. In this application, this application forms an evaluation system based on the supply characteristics of industrial products supplied by the industrial product supply accounts in the power industry and determines the dimension weights according to the industry characteristics of the power industry. The system can better fit the actual needs and characteristics of the power industry, thereby more accurately detecting the performance of the industrial product supply accounts in the industry. At the same time, by obtaining the detection data and evaluation rules, and combining the detection dimension weights for calculation, an objective evaluation based on data is achieved, human bias is reduced, and the detection accuracy is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 Flowchart of a method for detecting industrial product supply accounts for industrial products in the power industry in one embodiment;

[0050] Figure 2 A flowchart of a method for detecting industrial product supply accounts for industrial products in the power industry according to another embodiment;

[0051] Figure 3 This is a structural block diagram of an industrial product supply account detection device for industrial products in the power industry in one embodiment;

[0052] Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0054] In one embodiment, Figure 1 As shown, a method for detecting industrial product supply accounts for industrial products in the power industry is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0055] Step S102, obtain the industrial product supply characteristics of the industrial products of the power industry, and based on the industrial product supply characteristics, determine multiple detection dimensions for detecting the industrial product supply account of the industrial products of the power industry; the industrial product supply characteristics indicate the supply environment of the industrial product supply account supplying the industrial products of the power industry.

[0056] Among them, industrial product supply characteristics can indicate the specific environment and characteristics of industrial product supply accounts when providing MRO (maintenance, repair, and operations) industrial products in the power industry. The industrial product supply characteristics that constitute the power industry's industrial product supply environment can be determined through various methods, such as analyzing the characteristics of the power industry, studying power companies' demand for MRO supply accounts, and mining the operational data of existing industrial product supply platforms. These characteristics include, but are not limited to, information on the power industry's product category preferences, historical procurement behavior statistics, industry standards and regulatory requirements, and key evaluation factors for platform operational strategy setting.

[0057] The detection dimension can be the key aspect of detecting the performance of industrial product supply accounts in the industrial product supply environment of the power industry from different aspects and angles. The combination of multiple detection dimensions can form a multi-dimensional evaluation system, thereby more comprehensively reflecting the capabilities and value of the supply account.

[0058] For example, the terminal analyzes its internally stored environmental information and purchasing preference data related to the power industry. This data describes the typical requirements of the power industry for purchasing MRO (maintenance, repair, and operations) industrial products, such as requirements for product quality reliability, expectations for supply chain responsiveness, emphasis on the professional qualifications of supply accounts, and a preference for promoting the collaborative development of the platform ecosystem.

[0059] By analyzing this stored environmental information and purchasing preference data, the terminal can identify key supply characteristics. For example, the terminal might analyze historical purchasing records and discover that a power company frequently purchases a specific type of electrical component and has strict delivery deadlines for these components.

[0060] Based on the identification of these supply characteristics, the terminal determines multiple dimensions for testing industrial product supply accounts. The determination process is based on the detection and summarization of supply characteristics within the terminal, and the identified supply characteristics are refined into measurable detection dimensions. For example, if the terminal identifies the characteristic of strict time limit requirements for delivery cycle, order processing efficiency can be determined as a detection dimension. According to the technical briefing, the detection dimensions finally determined by the terminal may include ecological construction, order processing scale, supply account activity, order processing efficiency and penalty points, etc. These dimensions are considered to be key aspects that can comprehensively reflect the industrial product supply environment in the power industry.

[0061] Optionally, the terminal device may provide a user interface that allows the user to configure the selection of detection dimensions according to their specific needs or preferences. The user may use the user interface to check or uncheck preset detection dimensions or adjust the weights of the various detection dimensions.

[0062] Step S104: Determine the detection dimension weight corresponding to each detection dimension based on the industry characteristics of the power industry.

[0063] The power industry's characteristics can be seen as the essential attributes of its industrial product supply, including strict standards for product quality, a strong emphasis on supply chain stability, expectations for order processing efficiency, and consideration of the role of supply accounts in the industry ecosystem. These characteristics can be understood by analyzing internally stored industry environment information and purchasing preference data.

[0064] The detection dimension weight can be a numerical value assigned to each detection dimension, which is used to measure the relative importance of the dimension when detecting the industrial product supply account of the power industry. The numerical value reflects the influence of the dimension in the comprehensive detection.

[0065] For example, the terminal analyzes industry-specific data and assigns a specific weight to each identified detection dimension. For example, if the industry-specific data indicates that the power industry has a very high demand for supply chain stability, the terminal may assign a higher weight, such as 50%, to the directly related dimension of order processing scale, emphasizing the supply account's supply capacity and market share. If the industry-specific data also indicates that the power industry has a high demand for order processing efficiency, the order processing efficiency dimension may also be assigned a higher weight, such as 40%, to ensure that the supply account can respond quickly and efficiently process orders. If the industry-specific data indicates that the power industry encourages the development of the platform ecosystem, but it is not currently a core focus, the ecosystem construction dimension can be assigned a lower weight, such as 0, or set as a bonus point. The supply account activity dimension, which reflects the foundation of platform operations, can be assigned a moderate weight, such as 10%, to encourage supply accounts to actively participate in platform activities. Finally, given the power industry's strict requirements for compliance operations, a penalty coefficient, such as -5 to -2, can be set for the penalty deduction dimension to warn and punish violations.

[0066] Optionally, the terminal can perform big data analysis on industrial product order processing data for the power industry and, based on real-time industry trends and user feedback, dynamically adjust the weights of various monitoring dimensions. For example, if big data analysis reveals a significant increase in order processing demand for a certain key piece of equipment in the power industry, the weights of monitoring dimensions related to the supply capacity of that equipment (such as order processing volume and order processing efficiency) can be temporarily increased. Based on the re-determined dynamic weight information, the existing internal weight configuration is overwritten, and these new weights are used for subsequent supply account monitoring calculations. This mechanism of dynamically adjusting weights based on big data analysis and industry characteristics enables the evaluation system to more flexibly reflect actual market changes and the true needs of power companies, thereby more accurately measuring the actual value of supply accounts.

[0067] Step S106: Obtain the detection rules for each of the multiple detection dimensions and the detection data of the industrial product supply account under the multiple detection dimensions.

[0068] For example, the terminal can retrieve the detection rules corresponding to each detection dimension from the system or relevant data sources. These rules define how to measure and detect the supply account's performance along that detection dimension. It can also obtain the actual operational data of the industrial product supply account under inspection for these detection dimensions, reflecting the account's specific behavior and performance on the platform. Once these rules and data are obtained, subsequent detection calculations can be prepared.

[0069] Specifically, the detection rules can be pre-defined specific methods and standards for measuring and detecting each detection dimension, guiding how to use the acquired detection data to calculate the detection results under each detection dimension. These rules can define how to measure each detection dimension. For example, the order processing scale dimension can include the calculation method and standard values for the order processing amount, the number of order processing customers and the number of orders; the supply account activity dimension can be defined as the number of login days of the supply account corporate account; the order processing efficiency dimension can include the calculation formula and standard thresholds for order confirmation speed, shipment speed, delivery speed and collection speed; the penalty deduction dimension can involve indicators such as industrial product compliance rate and the number of violation penalty tickets.

[0070] Specifically, the detection data can be the actual performance data of the industrial product supply account under various detection dimensions, which is used to calculate the detection results of the account in various dimensions according to the detection rules. The terminal receives the identifier of the industrial product supply account that needs to be tested, which is selected by the user. Based on the identifier, the server is requested for relevant data of the account under various detection dimensions. For example, for the order processing scale dimension, the historical order processing amount, number of order processing customers and number of orders of the account can be requested; for the supply account activity dimension, the number of login days of the account can be requested; for the order processing efficiency dimension, the order confirmation time, delivery time, successful delivery time and collection time of the account can be requested; for the penalty deduction dimension, the industrial product compliance rate and violation penalty record of the account can be requested.

[0071] Step S108: Determine the detection results of each industrial product supply account based on the detection data, detection dimension weights and detection rules.

[0072] Exemplarily, the terminal first substitutes the acquired detection data of the industrial product supply account into the detection rules preset in the detection dimension for each detection dimension to perform calculations to obtain the specific detection results of the account in that dimension. Then, the terminal can combine the score or detection result calculated for each detection dimension with the predetermined weight of the dimension. The combination method is usually a weighted calculation, that is, multiplying the score of each dimension by its corresponding weight. Finally, the terminal can summarize all weighted dimension scores to obtain the final detection result of the industrial product supply account.

[0073] In this embodiment, this application determines the dimension weights based on the supply characteristics of industrial products supplied by the industrial product supply accounts in the power industry and the industry characteristics of the power industry. The evaluation system formed can better fit the actual needs and characteristics of the power industry, thereby more accurately detecting the performance of industrial product supply accounts in the industry. At the same time, by obtaining detection data and evaluation rules, and combining the detection dimension weights for calculation, an objective evaluation based on data is achieved, which reduces human bias and improves detection accuracy.

[0074] In an exemplary embodiment, after obtaining the detection rules of each of the multiple detection dimensions and the detection data of the industrial product supply account under the multiple detection dimensions, it also includes: determining the contribution of each detection indicator under the detection dimension to the detection dimension based on the industry characteristics of the power industry; based on the detection dimension weight and contribution, weighting each detection indicator to obtain the detection indicator weight corresponding to each detection indicator.

[0075] For example, when determining the contribution of each detection indicator within a detection dimension, the terminal can analyze the structured description of the multi-dimensional characteristics of the power industry to determine how these characteristics affect the importance of different indicators within that dimension for detecting supply accounts in the power industry supply environment. The terminal can analyze the relevant industry characteristics for each detection dimension and establish a mapping relationship between the characteristics and the contribution of the indicators. This mapping relationship can be based on predefined rules, industry knowledge graphs, or machine learning models.

[0076] In a specific embodiment, taking the order processing scale dimension as an example, the terminal can consider how the following industry characteristics of the power industry influence the contribution of its subordinate indicators. An industry characteristic might be that large-scale purchases are the norm, meaning that power companies typically purchase large amounts of industrial products. Therefore, when measuring the order processing scale of a supply account, the order processing amount metric can directly reflect its supply capacity and contribution to the platform's total order processing volume. Based on this characteristic, the terminal can determine that the order processing amount has a high contribution to the order processing scale dimension. An industry characteristic might be high customer concentration, meaning that purchasing entities in the power industry are relatively concentrated. In one embodiment, while serving multiple customers is important, it may not be as effective as the order processing amount of serving large customers in reflecting scale strength. Based on this characteristic, the terminal can determine that the contribution of the number of customers with orders processed is relatively lower than the order processing amount. An industry characteristic might be that demand stability is relatively important. A continuous and stable supply is crucial to ensuring power operations. While the individual order amount is important, the frequency of orders also reflects the stability and continuity of the partnership. Based on this characteristic, the terminal can determine that the contribution of the number of orders is between the order processing amount and the number of customers with orders processed, or is equivalent to the latter. Based on the above analysis, the terminal can quantify the impact of these industry characteristics on the importance of different indicators as contribution. For example, the contribution of order processing amount can be 70%, the number of order processing customers can be 20%, and the number of orders can be 10%.

[0077] Accordingly, based on the test data, test dimension weights, and test rules, the test results for each industrial product supply account are determined, including:

[0078] Determine the test results of the test dimension of the industrial product supply account based on the test indicator weights, test data and test rules.

[0079] For example, the terminal can traverse all detection indicators under each detection dimension. For each indicator, the actual detection data of the account can be obtained, and the detection result of the indicator can be calculated according to the preset calculation rules. The detection result of the indicator can then be multiplied by its corresponding detection indicator weight, and the weighted sum is performed to obtain the detection result of the supply account under the detection dimension.

[0080] In this example, by introducing detection indicators and contribution levels, and assigning more fine-grained weights, we can more accurately detect the performance of industrial product supply accounts across each detection dimension. This hierarchical weighting approach can more realistically reflect the demand priorities of the power industry, resulting in more accurate final detection results.

[0081] In an exemplary embodiment, the detection dimension includes an ecological construction dimension that reflects the degree of impact of an industrial product supply account on the supply environment. Based on the detection data, detection dimension weights, and detection rules, the detection results of each industrial product supply account are determined, including:

[0082] In the supply environment, the attractiveness of the industrial product supply account to other accounts is determined as the detection indicator under the ecological construction dimension; other accounts are accounts associated with the industrial product supply account in the supply chain of industrial products in the power industry; in the detection data, the number of user registrations corresponding to the detection indicator and the preset attraction coefficient are determined; calculations are performed based on the detection rules of the user registration number, attraction coefficient and ecological construction dimension to determine the detection results of the ecological construction dimension of each industrial product supply account.

[0083] Among them, the ecological construction dimension can be a detection dimension used to reflect the extent to which the industrial product supply account has a positive impact on the platform supply environment, such as its ability to attract other related accounts to join the platform. The attractiveness of the industrial product supply account to other accounts can be used as a detection indicator under the ecological construction dimension to measure the extent to which the industrial product supply account attracts relevant accounts upstream and downstream of the supply chain to register on the platform. Other accounts can be accounts in the supply chain of industrial products in the power industry that are associated with the detected industrial product supply account, such as the supply accounts, procurement accounts or partners it attracts. The number of user registrations can be the number of other accounts that the detected industrial product supply account directly or indirectly attracts to register on the platform. The attractiveness coefficient can be a pre-set value used to measure the average value or contribution of each newly registered user to the platform ecology.

[0084] For example, the terminal first identifies the detection indicator under the ecosystem construction dimension as the attractiveness of the industrial product supply account to other accounts within the supply environment. Further, data corresponding to this detection indicator can be extracted from the acquired detection data, including the number of user registrations attracted by the industrial product supply account and a preset attractiveness coefficient. Then, based on the detection rules preset for the ecosystem construction dimension, the acquired number of user registrations and attractiveness coefficient are combined to perform a calculation to determine the detection result of the industrial product supply account on this dimension. For example, the detection rule could be a simple formula: Ecosystem Construction Dimension Score = Number of User Registrations × Attractiveness Coefficient. Alternatively, the detection rule could take into account the differences in attractiveness of different account types and assign different attractiveness coefficients to different types of registered users, performing a weighted calculation. The calculated detection result for the ecosystem construction dimension can be combined with the detection results of other detection dimensions (such as order processing volume, supply account activity, order processing efficiency, and penalty points), and the overall detection result for the industrial product supply account can be determined based on the previously determined weights for each detection dimension.

[0085] In one embodiment, the weight of the ecological construction dimension can be 0, which means that the detection results of this dimension may not affect the total score in the current supply account detection. It can also be used as a reference indicator of the platform's ecological contribution to incentivize the supply account results and directly add points based on other detection results.

[0086] In this embodiment, by taking the attractiveness of the industrial product supply account to other accounts as a detection indicator of the ecological construction dimension, and calculating based on the number of user registrations and the attractiveness coefficient, the contribution of the supply account to the platform ecological construction can be quantified.

[0087] In an exemplary embodiment, the detection dimension includes an order processing efficiency dimension; based on the detection data, the detection dimension weights, and the detection rules, the detection results of each industrial product supply account are determined, including:

[0088] The processing speed of at least one key link in the order processing process of the industrial product supply account is determined as a detection indicator under the order processing efficiency dimension; in the detection data, the time data and the detection indicator weight assigned by the detection dimension weight are determined; the time data is used to indicate the processing speed of the key link in the order processing process; based on the detection rules of the time data, the detection indicator weight and the order processing efficiency dimension, the detection results of the order processing efficiency of each industrial product supply account are determined.

[0089] Among them, the order processing efficiency dimension can be used to measure the speed and efficiency of industrial product supply accounts in processing orders. The key links, under the order processing efficiency dimension, refer to the steps or stages that have a significant impact on the overall efficiency and customer experience of industrial product supply accounts in the process of completing an order. These links may include, but are not limited to, order confirmation, which can be the process of the supply account confirming the order information and starting processing after receiving the order from the purchasing account; order shipment, which can be the process of the supply account preparing the industrial products in the order and delivering them to the logistics service account for transportation, with the first shipment being the basis for shipment in batches; order delivery, which can be the process of the logistics service account successfully delivering the industrial products to the buyer's designated location; order collection, which can be the process of the supply account receiving the order payment from the buyer.

[0090] Exemplarily, the terminal first identifies that the detection indicator under the order processing efficiency dimension is the processing speed of at least one key link in the order processing process of the industrial product supply account. Next, the time data related to the selected key link can be extracted from the acquired detection data. For example, if the key link is order confirmation, the time data may record the specific length of time it takes for the order to be confirmed from the time the buyer places the order to the time the supply account confirms it. At the same time, the detection indicator weight previously assigned to the detection indicator can also be obtained, which reflects the importance of the processing speed of the key link in the entire order processing efficiency dimension. Then, according to the detection rules preset in the order processing efficiency dimension, the acquired time data and detection indicator weight can be combined for calculation to determine the detection result of the industrial product supply account in this dimension.

[0091] In one embodiment, the detection rule for the order processing efficiency dimension can be to set a benchmark value for each detection index and perform piecewise function scoring based on the benchmark value. For example, the order processing time of key links is divided into multiple intervals, each interval corresponding to a different score. The shorter the processing time, the higher the score. Finally, the detection results (scoring results) of each index are weighted and summed. Specifically, obtain the order data x corresponding to the evaluation index, set the benchmark value s1, and perform segmentation according to the benchmark value to obtain the first interval (0 < x <= s1), the second interval (s1 < x <= s2), and the third interval (s2 < x). Calculate the corresponding index scores in the three intervals, and finally perform weighted summation on the detection results (scoring results) of each index. In one embodiment, the time data corresponding to the order confirmation speed is x_confirmation, and the weight under the order processing efficiency dimension is W_confirmation. Calculate the scoring result y_confirmation according to the calculation rule. For example, s1 = 50, s2 = 60, q = W_confirmation; if 0 < x_confirmation <= 50, then y_confirmation = W_confirmation; if 50 < x_confirmation <= 60, then y_confirmation = W_confirmation / (50 - 60) * (x_confirmation - 60) = -W_confirmation * (x_confirmation - 60); if x_confirmation > 60, then y_confirmation = 0.

[0092] In this embodiment, by detecting the processing speed of the industrial product supply account in the key links of order processing, the fulfillment efficiency and service level can be directly reflected. As an important evaluation dimension, it can improve the accuracy of detecting the industrial product supply account.

[0093] In an exemplary embodiment, after determining the detection results of each industrial product supply account according to the detection data, detection dimension weights, and detection rules, it further includes:

[0094] Rank the industrial product supply accounts according to the detection results to obtain a ranking result; according to the ranking result, classify the industrial product supply accounts to obtain the detection level corresponding to the industrial product supply account, and display the detection level and the detection result.

[0095] Among them, the ranking result can be a list obtained by sorting according to the detection results of all industrial product supply accounts participating in the evaluation, reflecting the relative performance between supply accounts. The detection level can be a level identifier assigned to the supply account according to its position in the ranking result or the specific interval where its detection result is located.

[0096] For example, after the terminal calculates the final test results for all participating industrial product supply accounts, the test result can be a specific score, and these accounts can be sorted from high to low based on the test result score (higher scores, higher rankings). The sorting results can generate a list containing all participating accounts, arranged in order of their scores. If multiple accounts have the same score, pre-set rules can be used to handle the situation, such as secondary sorting by account ID, registration time, or other relevant information to ensure unique ranking.

[0097] The terminal can compare the ranking results of each industrial product supply account with the preset grading rules to determine the detection level to which the account belongs. The terminal has preset grading rules that define the levels corresponding to different ranking ranges or score intervals. For example: accounts ranked in the top 10% are classified as five stars. Accounts ranked between 10% and 30% are classified as four stars. Accounts ranked between 30% and 50% are classified as three stars. Accounts ranked between 50% and 80% are classified as two stars, and accounts ranked in the bottom 80% are classified as one star.

[0098] The terminal can then display the account's detection level and specific detection results to the user through the user interface. The display method can use text, icons or other visual forms to enable the user to clearly understand the performance level of the account in the evaluation system.

[0099] In this embodiment, by ranking and grading industrial product supply accounts, complex detection results can be converted into a more intuitive and easy-to-understand form, allowing users to quickly understand the overall performance level of different supply accounts. The supply account rankings are displayed in star-rated rankings, allowing managers to quickly grasp the supplier situation and improve management efficiency.

[0100] In an exemplary embodiment, displaying the detection level and detection results further includes:

[0101] According to the preset update time, the displayed test results and test levels are updated to obtain the updated test results and test levels of the industrial product supply account;

[0102] If the updated inspection result and / or inspection level of the industrial product supply account meets the preset incentive standard, incentive prompt information is generated, and the incentive prompt information includes incentive measures for the industrial product supply account.

[0103] Exemplarily, the terminal is internally configured with a preset update schedule, such as regular updates every day, every week, or every month. When the set update time is reached, a new round of detection process can be automatically started, including re-acquiring the latest detection data, calculating the updated detection results according to the preset detection rules and weights, and re-ranking and grading based on the updated detection results. In addition, the above process can also be executed immediately in response to the user's manual update request. After the update is completed, the detection results and detection levels of the industrial product supply account displayed on the interface can be replaced with the latest calculated detection results and detection levels.

[0104] The terminal has preset incentive criteria. These criteria can be based on updated test results (for example, test results reaching a certain threshold score), an improvement in test level (for example, from three stars to five stars), or a significant improvement in ranking. After the terminal completes the test results and level update for an industrial product supply account, it can compare the updated data with the preset incentive criteria. If any of the incentive criteria are met, an incentive prompt message can be generated. This prompt message can include specific incentive measures. The generated incentive prompt message can be displayed to the corresponding industrial product supply account through the user interface as a pop-up window, notification, or other eye-catching method, informing them of the incentives they have received for their outstanding performance.

[0105] In this embodiment, by regularly updating test results and grades, we can reflect the latest performance of industrial product supply accounts, maintaining the dynamic and effective nature of the testing system. The introduction of an incentive mechanism can effectively encourage supply accounts to improve service quality and actively participate in platform operations, thereby promoting the healthy development of the platform ecosystem.

[0106] In an exemplary embodiment, Figure 2 As shown in the figure, the process of the terminal detecting the industrial product supply account includes:

[0107] Step S201: Based on the supply characteristics of industrial products, multiple detection dimensions are determined for testing industrial product supply accounts. The terminal analyzes environmental information and purchasing preference data related to the power industry. This data describes the typical requirements of the power industry for MRO industrial product procurement, such as requirements for product quality reliability, expectations for supply chain responsiveness, emphasis on the professional qualifications of supply accounts, and a preference for promoting the coordinated development of the platform ecosystem. By analyzing this data, the terminal identifies key supply characteristics, such as strict deadlines for delivery cycles and the need for specific industry certifications. Based on these supply characteristics, the terminal determines multiple dimensions for testing industrial product supply accounts, including: ecosystem construction, order processing scale, supply account activity, order processing efficiency, and penalty points. The ecosystem construction dimension is used to test the attractiveness of industrial product supply accounts to other accounts in the supply environment. Other accounts are upstream and downstream enterprise users related to the industrial product supply account registered on the platform, including purchasing and supply account users. The ecosystem construction dimension reflects the influence of the industrial product supply account in the industry ecosystem. The order processing scale dimension is used to detect the business volume and market share of industrial product supply accounts. Its detection indicators include order processing amount, number of order processing customers, and number of orders. The supply account activity dimension is used to detect the participation and response time of industrial product supply accounts on the platform. Its detection indicators include the number of times industrial product supply accounts log in to the platform. The order processing efficiency dimension is used to detect the operational efficiency of industrial product supply accounts. Its detection indicators include order confirmation speed, shipping speed, successful delivery speed, and collection speed. The penalty deduction dimension is used to detect the compliance of industrial product supply accounts. Its detection indicators include the proportion of industrial products removed from the shelves and the number of penalty notices for violations.

[0108] In step S202, the terminal determines the detection dimension weights of each detection dimension based on the industry characteristics of the electric power industry. The terminal analyzes the industry characteristic data, which implies the degree of importance the electric power industry attaches to different dimensions and their subordinate indicators. Specifically, the detection dimension weight of the ecological construction dimension can be 0%, the detection dimension weight of the penalty deduction dimension can be 0%, the detection dimension weight of the order processing scale dimension can be 50%, the detection dimension weight of the supply account activity dimension can be 10% or more, and the detection dimension weight of the order processing efficiency dimension can be 40%. Specifically, in the ecological construction dimension, a reward mechanism can be set, and the attractiveness coefficient and the upper limit of the reward score can be set to reflect its importance to the ecological construction of the supply account, thereby affecting the final detection results. In the penalty deduction dimension, the corresponding penalty benchmark value can be set for the proportion of industrial products removed from the shelves and the number of violation penalty tickets, and the penalty coefficient can be preset to constrain the compliance operation of the supply account.

[0109] Step S203 determines the contribution of each detection indicator under each detection dimension based on the industry characteristics of the power industry, and determines the detection indicator weight based on the contribution. The terminal analyzes the industry characteristics of the power industry to determine the importance of each detection indicator under each detection dimension to measuring the overall performance of that dimension, thereby determining its contribution. The terminal calculates the specific weight of each detection indicator based on the total weight of each detection dimension and the contribution ratio of each detection indicator under it. For example, if the order processing scale dimension has a weight of 50%, and the contribution ratios of the order processing amount, number of order processing customers, and number of orders are assumed to be 80%, 10%, and 10%, respectively, then the detection indicator weights of these indicators are 40%, 10%, and 10%, respectively. If the order processing efficiency dimension has a weight of 40%, and the contribution ratios of the order confirmation speed, order shipment speed, order delivery speed, and order collection speed are assumed to be 25%, 25%, 25%, and 25%, respectively, then the detection indicator weights of these indicators are 10%, 10%, 10%, and 10%, respectively.

[0110] Step S204: Acquire the detection rules and detection data corresponding to each detection dimension. The terminal acquires the detection rules, which define how to measure the detection indicators under each detection dimension. For the order processing scale dimension, the detection rules instruct the following operations: determine the detection indicators for the order processing scale dimension (the supply account's order processing amount, number of order processing customers, and number of orders), and read the detection data corresponding to the detection indicators; divide these data by the corresponding preset standard values, and multiply the results by the corresponding weights to obtain the scoring data for the order processing scale dimension. Specifically, the order processing amount, number of order processing customers, and number of orders of the supply account are obtained and compared with the preset standard values (the standard value for order processing amount is 2 million yuan, the standard value for number of order processing customers is 10, and the standard value for number of orders is 10). The dimension score of each indicator is calculated using the formula y=x / s*q, where x is the indicator value, s is the corresponding standard value, and q is the corresponding weight score. The highest detection indicator weight assigned to each indicator is q. For the supply account activity dimension, the evaluation rules instruct the following operations: determine the supply account activity indicator (number of days the supply account's business account is logged in) and retrieve the corresponding test data; divide the login days data by a preset standard value and multiply the result by the corresponding weighted score to obtain the supply account activity dimension score. Specifically, the score for this dimension is calculated by obtaining the number of days the supply account's business account is logged in, comparing it with the preset standard value (20 days), and using the formula y = x / s*q, where x is the number of days logged in, s is the standard value 20, and q is the corresponding weighted score, with the maximum score for this dimension being q. For the penalty deduction dimension, the evaluation rules perform the following operations: retrieve the number of industrial products removed from the supply account due to audits and the number of penalty notices issued to the supply account; and multiply these data by the corresponding preset penalty deduction standard values to obtain the penalty deduction dimension score. Specifically, the score for this dimension is calculated based on the preset standard values (the compliance penalty coefficient for industrial products is -5 and the penalty coefficient for supply accounts is -2) and the formula. The formula for calculating the compliance rate for industrial products is y = x * s, with the highest dimension score being -5. The formula for calculating the penalty for supply accounts is y = x * s.

[0111] At the same time, the terminal receives the identifier of the industrial product supply account selected by the user that needs to be tested, and requests the platform server for relevant test data of the account under various test dimensions. The platform server collects the relevant data of the supply account in real time, and after cleaning, conversion and standardization, stores it in the data warehouse to ensure data accuracy and availability.

[0112] Step S205, based on the detection data, detection dimension weights, detection indicator weights and detection rules, determines the detection results of each industrial product supply account. For each detection dimension, the terminal substitutes the acquired detection data of the industrial product supply account into the detection rules preset in the detection dimension for calculation, and obtains the specific detection results of the account in this dimension. Then, the score or detection result calculated for each detection dimension can be combined with the weight predetermined for the dimension. The combination method is usually weighted calculation, that is, the score of each dimension is multiplied by its corresponding weight. Finally, all weighted dimension scores can be summarized to obtain the final detection result of the industrial product supply account.

[0113] In step S206, based on the test results of the industrial product supply accounts, the terminal determines the ranking and test grade of each supply account and displays them. The terminal sorts all participating industrial product supply accounts based on the final test results (the total score of each dimension weighted by the dimension weights) and generates a ranking list. Based on the account's position in the ranking list, the terminal categorizes each account into different grades (e.g., excellent, good, qualified, or unqualified) and displays the supply account's test grade and specific test results on the interface.

[0114] In step S207, the displayed test results and test grades are updated according to the preset update schedule, and incentive notification information is determined based on the updated test results and test grades. The terminal re-executes all of the above steps at a preset interval (e.g., daily), updating the test results and grades for all supply accounts. If the updated results meet the preset incentive criteria (e.g., the grade is upgraded to Excellent), the terminal generates a notification message containing incentives (e.g., platform traffic support) and displays it to the corresponding supply account.

[0115] In this embodiment, multi-dimensional quantitative evaluation is combined with dynamic weight allocation to make the evaluation results more scientific and accurate, providing a reliable basis for supply account management; intelligent calculation and visual display greatly reduce manual workload and improve management efficiency; through hierarchical management and incentive mechanisms, supply accounts are encouraged to improve service quality and compliance levels, ensuring healthy competition in the power industry supply chain, providing an advanced example for the management of industrial product sales supply accounts in the power industry, and promoting the improvement of the industry's supply chain management level.

[0116] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0117] Based on the same inventive concept, embodiments of the present application also provide a device for detecting industrial product supply accounts for industrial products in the power industry, which is used to implement the aforementioned method for detecting industrial product supply accounts for industrial products in the power industry. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in one or more embodiments of the device for detecting industrial product supply accounts for industrial products in the power industry provided below can be found in the limitations of the method for detecting industrial product supply accounts for industrial products in the power industry, and will not be repeated here.

[0118] In an exemplary embodiment, Figure 3 As shown, a device for detecting supply accounts of industrial products in the power industry is provided, comprising: a supply feature recognition module 310, a detection dimension construction module 320, a detection data collection and rule configuration module 330, and a supply account detection result determination module 340, wherein:

[0119] The supply feature identification module 310 is used to obtain the industrial product supply characteristics of the industrial products in the power industry, and based on the industrial product supply characteristics, determine multiple detection dimensions for detecting the industrial product supply account of the industrial products in the power industry; the industrial product supply characteristics indicate the supply environment in which the industrial product supply account supplies the industrial products in the power industry.

[0120] The detection dimension construction module 320 is used to determine the detection dimension weight corresponding to each detection dimension according to the industry characteristics of the power industry.

[0121] The detection data collection and rule configuration module 330 is used to obtain the detection rules of each of the multiple detection dimensions and the detection data of the industrial product supply account under the multiple detection dimensions.

[0122] The supply account detection result determination module 340 is used to determine the detection result of each of the industrial product supply accounts based on the detection data, the detection dimension weights and the detection rules.

[0123] In one embodiment, the detection dimension construction module 320 is also used to determine the contribution of each detection indicator under the detection dimension to the detection dimension based on the industry characteristics of the power industry; based on the detection dimension weight and the contribution, the weight of each detection indicator is assigned to obtain the detection indicator weight corresponding to each detection indicator.

[0124] In one embodiment, the supply account detection result determination module 340 is further used to determine the detection result of the detection dimension of the industrial product supply account based on the detection indicator weight, the detection data and the detection rule.

[0125] In one embodiment, the detection dimension includes an ecological construction dimension that reflects the degree of influence of the industrial product supply account on the supply environment; the detection dimension construction module 320 is also used to determine the attractiveness of the industrial product supply account to other accounts under the supply environment as a detection indicator under the ecological construction dimension; the other accounts are accounts associated with the industrial product supply account in the supply chain of industrial products in the power industry; in the detection data, the number of user registrations corresponding to the detection indicator and the preset attraction coefficient are determined; calculations are performed based on the number of user registrations, the attraction coefficient and the detection rules of the ecological construction dimension to determine the detection results of the ecological construction dimension of each of the industrial product supply accounts.

[0126] In one embodiment, the detection dimension includes an order processing efficiency dimension; the detection dimension construction module 320 is also used to determine the processing speed of at least one key link in the order processing process of the industrial product supply account as a detection indicator under the order processing efficiency dimension; in the detection data, determine the time data and the detection indicator weight assigned by the detection dimension weight; the time data is used to indicate the processing speed of the key link in the order processing process; based on the time data, the detection indicator weight and the detection rules of the order processing efficiency dimension, determine the detection results of the order processing efficiency of each industrial product supply account.

[0127] In one embodiment, the supply account detection result determination module 340 is also used to rank the industrial product supply accounts according to the detection results to obtain ranking results; classify the industrial product supply accounts according to the ranking results to obtain the detection level corresponding to the industrial product supply accounts, and display the detection level and the detection results.

[0128] In one embodiment, the supply account detection result determination module 340 is also used to update the displayed detection results and the detection level according to a preset update time to obtain the updated detection results and detection level of the industrial product supply account; if the updated detection results and / or the detection level of the industrial product supply account meet the preset incentive standards, incentive prompt information is generated, and the incentive prompt information includes incentive measures for the industrial product supply account.

[0129] Each module in the aforementioned power industry industrial product supply account detection device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0130] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 4 As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for detecting industrial product supply accounts for industrial products in the power industry.

[0131] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0132] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0133] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0134] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0135] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0136] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, artificial intelligence (AI) processors, and the like.

[0137] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0138] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for detecting industrial product supply accounts for industrial products in the power industry, characterized in that: The method comprises: Acquiring industrial product supply characteristics of an industrial product in the power industry, and determining multiple detection dimensions for detecting an industrial product supply account for the industrial product in the power industry based on the industrial product supply characteristics; the industrial product supply characteristics indicate a supply environment in which the industrial product supply account supplies the industrial product in the power industry; Determine the detection dimension weights corresponding to each of the detection dimensions according to the industry characteristics of the power industry; Obtaining detection rules for each of the plurality of detection dimensions and detection data of the industrial product supply account under the plurality of detection dimensions; The detection results of each of the industrial product supply accounts are determined based on the detection data, the detection dimension weights and the detection rules.

2. The method according to claim 1, characterized in that After obtaining the detection rules of each of the plurality of detection dimensions and the detection data of the industrial product supply account under the plurality of detection dimensions, the method further includes: Determining, based on the industry characteristics of the power industry, the contribution of each detection indicator under the detection dimension to the detection dimension; Based on the detection dimension weight and the contribution, weights are assigned to the detection indicators to obtain detection indicator weights corresponding to the detection indicators; Determining the detection results of each of the industrial product supply accounts based on the detection data, the detection dimension weights, and the detection rules includes: The detection result of the detection dimension of the industrial product supply account is determined based on the detection indicator weight, the detection data and the detection rules.

3. The method according to claim 2, characterized in that The detection dimension includes an ecological construction dimension that reflects the degree of impact of the industrial product supply account on the supply environment; the detection result of each industrial product supply account is determined based on the detection data, the detection dimension weight and the detection rules, including: The attractiveness of the industrial product supply account to other accounts in the supply environment is determined as a detection indicator under the ecological construction dimension; the other accounts are accounts associated with the industrial product supply account in the supply chain of the power industry industrial products; In the detection data, determining the number of user registrations corresponding to the detection indicator and a preset attraction coefficient; Calculation is performed based on the number of user registrations, the attractiveness coefficient, and the detection rules of the ecological construction dimension to determine the detection results of the ecological construction dimension of each of the industrial product supply accounts.

4. The method according to claim 2, characterized in that The detection dimension includes an order processing efficiency dimension; and determining the detection result of each industrial product supply account based on the detection data, the detection dimension weights, and the detection rules includes: Determining the processing speed of at least one key link in the order processing process of the industrial product supply account as a detection indicator under the order processing efficiency dimension; In the detection data, time data and the detection indicator weight assigned by the detection dimension weight are determined; the time data is used to indicate the processing speed of the key link in the order processing process; Based on the time data, the detection indicator weights and the detection rules of the order processing efficiency dimension, the detection results of the order processing efficiency of each of the industrial product supply accounts are determined.

5. The method according to claim 1, characterized in that: After determining the detection results of each of the industrial product supply accounts based on the detection data, the detection dimension weights, and the detection rules, the method further includes: Ranking the industrial product supply accounts according to the detection results to obtain a ranking result; According to the ranking results, the industrial product supply accounts are graded to obtain the detection grades corresponding to the industrial product supply accounts, and the detection grades and the detection results are displayed.

6. The method according to any one of claims 1 to 5, characterized in that Displaying the detection level and the detection result also includes: Update the displayed test results and test levels according to a preset update time to obtain updated test results and test levels of the industrial product supply account; If the updated detection result and / or the detection level of the industrial product supply account meets the preset incentive standard, incentive prompt information is generated, and the incentive prompt information includes incentive measures for the industrial product supply account.

7. An industrial product supply account detection device for industrial products in the power industry, characterized in that: The device comprises: A supply feature identification module is configured to obtain industrial product supply features of power industry industrial products and, based on the industrial product supply features, determine multiple detection dimensions for detecting the industrial product supply account of the power industry industrial products; the industrial product supply features indicate the supply environment in which the industrial product supply account supplies the power industry industrial products; A detection dimension construction module is used to determine the detection dimension weight corresponding to each detection dimension according to the industry characteristics of the power industry; A detection data collection and rule configuration module, configured to obtain detection rules for each of the plurality of detection dimensions, and detection data of the industrial product supply account under the plurality of detection dimensions; The supply account detection result determination module is used to determine the detection results of each industrial product supply account based on the detection data, the detection dimension weights and the detection rules.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images