An intelligent supply chain risk early warning system based on multi-source data fusion

Abstract

This invention discloses an intelligent supply chain risk early warning system based on multi-source data fusion, belonging to the field of supply chain early warning technology. The invention includes a data acquisition module, a supply chain analysis module, a risk early warning module, and a database. It identifies the industries in which an enterprise's supply chain operates and acquires the related industries of each industry. Based on the historical capacity changes of each related industry and the current capacity changes of each related industry, it determines whether the industries in which the supply chain operates are negatively impacted by other industries. If not negatively impacted, it determines the enterprise's supply chain risk based on the supply relationships and supply situations of each supplier and other end-user enterprises. If negatively impacted, it determines the enterprise's supply chain risk based on the probability of breach of contract by each supplier, thus ensuring the accuracy and timeliness of supply chain identification.

Description

Technical Field

[0001] This invention relates to the field of supply chain early warning technology, specifically to an intelligent supply chain risk early warning system based on multi-source data fusion. Background Technology

[0002] Modern supply chains have evolved into complex global network structures involving suppliers, distributors, and retailers. As supply chain complexity continues to increase, various risk events occur frequently, which may lead to supply chain disruptions and cause huge economic losses to enterprises.

[0003] Most existing intelligent supply chain risk early warning systems based on multi-source data fusion analyze the risks of a company's supply chain based on a single supply chain between the company and its suppliers, and only within the industry in which the company operates. Obviously, such intelligent supply chain risk early warning systems have at least the following shortcomings: 1. Existing technology analyzes the risk of a company's supply chain based on a single supply chain between the company and its suppliers. However, in reality, a supplier can supply products to multiple companies. When a supplier supplies products to multiple companies, the supply to multiple companies by the supplier affects each other. Existing technology ignores this point, and therefore cannot guarantee the accuracy of supply chain risk identification.

[0004] 2. Existing technologies only analyze supply chain risks within the industrial environment in which the enterprise operates. However, the development of different industries influences each other, and the development of some industries may have a negative or positive impact on others. Existing technologies ignore the impact of external industries on the industrial cluster in which the enterprise's supply chain is located. When external developments change, it is impossible to identify their impact on the enterprise's supply chain in a timely manner, and the timeliness and accuracy of supply chain identification cannot be guaranteed. Summary of the Invention

[0005] In view of the above-mentioned technical shortcomings, the purpose of this invention is to provide an intelligent supply chain risk early warning system based on multi-source data fusion.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides an intelligent supply chain risk early warning system based on multi-source data fusion, including: a data acquisition module, a supply chain analysis module, a risk early warning module, and a database.

[0007] The data acquisition module is used to obtain the company's supply chain information from the database.

[0008] The supply chain analysis module is used to obtain the supply relationships of each supplier and other end-user companies of each supplier from the enterprise's supply chain information, obtain the current production capacity of other industries, analyze the impact of other industries on the enterprise's supply chain, obtain the product demand of the enterprise and other end-user companies of each supplier, and analyze whether the risk of the enterprise's supply chain is too great.

[0009] The risk warning module is used to issue an early warning when the enterprise's supply chain risk is high.

[0010] The database is used to store supply chain information, the production capacity of each industry in different historical time periods, the total production capacity of each industry in the previous time period, the reasons for each supplier's failure to meet the supply standards when supplying products to the company in previous periods and the supply situation to the company, as well as information on each supplier's breach of contract in previous periods and the highest product price that the company can offer to each supplier.

[0011] The beneficial effects of this invention are as follows: 1. This invention provides an intelligent supply chain risk early warning system based on multi-source data fusion, which identifies the industries in which an enterprise's supply chain is located, and obtains the related industries of each industry. Based on the historical capacity changes of each related industry and the current capacity changes of each related industry, it determines whether the industries in which the supply chain is located are negatively impacted by other industries. If they are not negatively impacted by other industries, it determines whether the enterprise's supply chain risk is high based on the supply relationship and supply situation of each supplier and other end enterprises. If they are negatively impacted by other industries, it determines whether the enterprise's supply chain risk is high based on the probability of each supplier defaulting on its contracts, thus ensuring the accuracy and timeliness of supply chain identification.

[0012] 2. This invention refers to each industry included in the enterprise's supply chain as a marked industry and other industries as industries to be analyzed. Based on the production capacity of each industry to be analyzed and the production capacity of each marked industry in different historical time periods, related industries are obtained, and the production capacity relationship between each marked industry and each related industry is analyzed. Based on the analysis results and the current changes in the production capacity of each related industry, it is analyzed whether the current related industries have a negative impact on the supply chain. Based on the analysis results, a supply chain risk identification method is set to ensure the accuracy and timeliness of supply chain identification.

[0013] 3. When the related industries do not negatively impact the supply chain, this invention determines whether the product supply meets the standards. When it does, it indicates that the enterprise's supply chain risk is low. When it does not meet the standards, it determines whether the supply chain risk is high based on the impact of the marked supplier's product supply to its marked terminal enterprises on the enterprise's product supply. When the related industries negatively impact the supply chain, the suppliers that are negatively impacted are referred to as the affected suppliers. The probability of each affected supplier defaulting on its contract is used to determine whether the supply chain risk is high, thus ensuring the accuracy of supply chain identification. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 As shown, the present invention provides an intelligent supply chain risk early warning system based on multi-source data fusion, including: a data acquisition module, a supply chain analysis module, a risk early warning module, and a database.

[0018] The data acquisition module is connected to the supply chain analysis module, the supply chain analysis module is connected to the risk warning module, and the database is connected to both the data acquisition module and the supply chain analysis module.

[0019] The data acquisition module is used to obtain the company's supply chain information from the database.

[0020] It should be noted that the company's supply chain information includes the supply relationships of various industries and suppliers included in the supply chain, the product supply data of each supplier to its respective labeling terminal enterprises and the enterprise itself, as well as the product demand of each labeling terminal enterprise and the enterprise itself.

[0021] It should also be noted that the product supply data includes the quantity of products provided by each supplier, the quality of the products provided, and the compliance of the products.

[0022] Among them, the enterprise's product demand refers to the enterprise's requirements for the quantity, quality, and compliance of products supplied by each supplier.

[0023] It is important to know that "other end-user companies" of a supplier refers to other entities to which the supplier also provides products, besides the company in question.

[0024] The supply chain analysis module is used to obtain the supply relationships of each supplier and other end-user companies of each supplier from the enterprise's supply chain information, obtain the current production capacity of other industries, analyze the impact of other industries on the enterprise's supply chain, obtain the product demand of the enterprise and other end-user companies of each supplier, and analyze whether the enterprise's supply chain is risky.

[0025] In one specific embodiment, the supply chain analysis module includes an industry impact analysis unit and a risk monitoring unit.

[0026] The industry impact analysis unit is used to obtain the industries included in the enterprise's supply chain, refer to the industries in the market other than those included in the supply chain as other industries, select related industries from other industries, and determine whether the related industries have a negative impact on the enterprise's supply chain based on the current production capacity of each related industry.

[0027] In a specific embodiment, the process of selecting related industries from other industries is as follows: other industries are referred to as industries to be analyzed, and the industries included in the enterprise's supply chain are referred to as marked industries. The products of each marked industry and each industry to be analyzed, as well as the product flow of each industry to be analyzed, are obtained. The selection conditions for related industries are: (1) if the product of a certain industry to be analyzed is a competitor of the product of a certain marked industry, then the industry to be analyzed is a related industry; (2) if the product flow of a certain industry to be analyzed includes a certain marked industry, then the industry to be analyzed is a related industry. When a certain industry to be analyzed meets any one of the selection conditions for related industries, the industry to be analyzed is a related industry. The related industries are selected by this method.

[0028] It should be noted that staff obtained information on the product flow of each industry to be analyzed through market research.

[0029] It should also be noted that competing products refer to two products that are mutually competitive but can be substituted for each other. For example, photovoltaic silicon wafers and semiconductor silicon wafers are competing products. This example is for illustrative purposes only and is not the only one.

[0030] In another specific embodiment, the process of determining whether each related industry has a negative impact on the enterprise's supply chain is as follows: The production capacity of each related industry and each marked industry in different historical time periods is obtained from the database, plotted on a curve graph, and marked with different colors. Based on the changes in the production capacity of each related industry in the curve graph, the production capacity increment of the related industry is calculated. Similarly, the production capacity increment of the marked industry is calculated. The production capacity increment includes 1 and -1. When the production capacity increment of the related industry is the same as the production capacity increment of the marked industry, it indicates that the production capacity of each marked industry is positively correlated with the production capacity of each related industry; otherwise, it indicates a negative correlation.

[0031] It should be noted that the x-axis of this graph represents each historical time period, and the y-axis represents production capacity.

[0032] Specifically, the starting and ending y-axis values ​​of a certain related industry curve in the graph are obtained. The starting y-axis value is subtracted from the ending y-axis value to obtain the capacity change value of the related industry. The capacity change values ​​of each related industry are calculated in this way. The capacity change values ​​of each related industry are added together to obtain the total capacity change value of each related industry. If the total capacity change value of each related industry is >0, the capacity increment of the related industry is 1. If the total capacity change value of each related industry is ≤0, the capacity increment of the related industry is -1.

[0033] The database is used to obtain the total capacity of each related industry in the previous period and the total capacity of each related industry at present. The capacity increment of the current related industry is determined. Based on the capacity increment of the current related industry and the relationship between the capacity of each marked industry and the capacity of each related industry, the industry impact value is determined. If the industry impact value is 1, it means that each related industry has a negative impact on the enterprise's supply chain. If the industry impact value is 0, it means that each related industry has no negative impact on the enterprise's supply chain.

[0034] The process for determining the industry impact value described above is as follows: If the current capacity increase of the related industries is 1, and the capacity of each marked industry is positively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry has increased, and the industry impact value is 0.

[0035] If the current capacity increment of related industries is 1, and the capacity of each marked industry is negatively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry decreases, and the industry shock value is 1.

[0036] If the current capacity increment of related industries is -1, and the capacity of each marked industry is positively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry decreases, and the industry shock value is 1.

[0037] If the current capacity increment of related industries is -1, and the capacity of each marked industry is negatively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry has increased, and the industry shock value is 0.

[0038] The risk monitoring unit is used to analyze whether the risk of the enterprise's supply chain is too high when the related industries do not have a negative impact on the enterprise's supply chain, based on the supply data of each supplier, the product demand of each marking terminal enterprise and the enterprise itself; and when the related industries have an impact on the enterprise's supply chain, it analyzes whether the risk of the enterprise's supply chain is high based on the impact of the related industries.

[0039] In a specific embodiment, when the related industries do not have a negative impact on the enterprise's supply chain, the risk of the enterprise's supply chain is determined. The specific process is as follows: A11. Obtain the product supply data of each supplier to its respective marked terminal enterprises and the enterprise, as well as the product demand of each marked terminal enterprise and the enterprise, and determine whether the product supply meets the standards. When it meets the standards, it means that the enterprise's supply chain risk is small. When it does not meet the standards, the suppliers whose product supply does not meet the standards are called each marked supplier, and the reasons for the non-compliance of each marked supplier and the objects of the non-compliance of product supply are obtained.

[0040] It should be noted that when the product supply data of each supplier meets the product requirements of each of its respective labeling terminal enterprises, it means that the product supply meets the standards; otherwise, it means that the product supply does not meet the standards.

[0041] It should also be noted that a supplier whose product supply does not meet the standards refers to a supplier that fails to meet the product requirements of one or more of its end-user companies.

[0042] The reasons for supply failure include substandard quality, substandard quantity, and substandard compliance. Substandard quality means that the quality of the products provided by the supplier does not meet the requirements of the end-user company. Similarly, other reasons for supply failure can be identified.

[0043] It is important to know that the entities marked as having substandard products supplied by suppliers are end-user companies whose products do not meet their product requirements.

[0044] A12. If one or more marked suppliers fail to meet the requirements and include the enterprise, it indicates that the enterprise has a high supply chain risk. Conversely, based on the reasons for the failure of each marked supplier to meet the requirements, analyze whether the supply of products from each marked supplier to its respective marked end enterprise will affect the supply of products to the enterprise. If it will affect the supply, it indicates that the enterprise has a high supply chain risk. Conversely, it indicates that the enterprise has a low supply chain risk.

[0045] The above-mentioned analysis of whether the product supply of each marking supplier to its respective marking terminal enterprise will affect the product supply to that enterprise is as follows: For a certain marking supplier, the reasons for the substandard supply in each of the past product supply times of the marking supplier to the enterprise are obtained from the database. Based on the reasons for the substandard supply of the marking supplier, similar historical supply is determined. The supply situation of the marking supplier to the enterprise in each similar historical supply is obtained from the database. If the supply situation of the marking supplier to the enterprise is good in each similar historical supply, it means that the product supply of the marking supplier to its respective marking terminal enterprise will not affect the product supply to that enterprise. Conversely, it means that the product supply of the marking supplier to its respective marking terminal enterprise will affect the product supply to that enterprise.

[0046] It should be noted that the "historical supply of products to the company by the marked supplier" here refers to the fact that the products supplied by the marked supplier to the company that did not meet the standards do not include the company's historical product supply to the company.

[0047] It should also be noted that each historical instance of supplying products to the company with the same reason for non-compliance as the current reason for non-compliance of the marked supplier is referred to as a similar historical supply.

[0048] The supply situation is categorized into good and poor supply situations, and staff assess the supply situation based on the company's product demand.

[0049] This method is used to determine whether the product supply of each marking supplier to its respective marking terminal enterprise will affect the product supply to that enterprise.

[0050] In another specific embodiment, when the related industries have a negative impact on the enterprise's supply chain, the risk of the enterprise's supply chain is determined. The specific process is as follows: A21, each supplier that is negatively impacted is referred to as the affected supplier, and the marked terminal enterprises of each affected supplier and the enterprise's product supply demand for each affected supplier are obtained.

[0051] It should also be noted that the industry impact value of each supplier's corresponding industry is obtained, and suppliers with an industry impact value of 1 are negatively impacted.

[0052] A22. Based on the terminal enterprises of each affected supplier and the supply demand of each enterprise for the products of each affected supplier, determine whether the probability of each affected supplier defaulting on the contract is high. If there are affected suppliers with a high probability of defaulting on the contract, it means that the enterprise has a high supply chain risk. Conversely, if there are no affected suppliers with a high probability of defaulting on the contract, it means that the enterprise has a low supply chain risk.

[0053] The above-mentioned process for determining whether the probability of each affected supplier breaching the contract is high is as follows: For a certain affected supplier, A31, obtain the product supply demand of each marked terminal enterprise of the affected supplier and the product supply demand of the enterprise to the affected supplier, calculate the proportion of the enterprise's product supply demand, and obtain the information on the affected supplier's historical breaches of contract from the database, and analyze the calculation relationship between the probability of the affected supplier's breach of contract and the proportion of the enterprise's product supply demand and the price.

[0054] It should be noted that the information on each breach of contract includes the percentage of the affected supplier's product supply demand, price, and probability of breach of contract in each of the previous breaches of contract by the affected supplier.

[0055] A32. Obtain the highest product price that the company can offer to this supplier from the database. Based on the company's product supply demand ratio, the highest product price that can be offered, and the calculation relationship obtained in step A31, obtain the probability of the affected supplier defaulting on the contract. Compare this probability with a preset default probability threshold. If the probability is greater than the preset default probability threshold, it means that the affected supplier has a high probability of defaulting on the contract. Conversely, if the probability is lower, it means that the affected supplier has a low probability of defaulting on the contract. Use this method to determine whether the probability of each affected supplier defaulting on the contract is high.

[0056] It should be noted that the preset default probability threshold is a critical value used to determine whether the probability of the affected supplier defaulting is high, and its specific value is set by the staff according to the company's operating status.

[0057] The above-mentioned analysis of the probability of breach of contract by the affected supplier and the calculation relationship between the proportion of product supply demand and price of the enterprise are as follows: obtain the proportion of product supply demand, price and probability of breach of contract of the affected supplier in each of the historical breaches of contract, and construct each data pair, which consists of the proportion of product supply demand and price.

[0058] It should be noted that the staff obtained the probability of suppliers defaulting on contracts in each of their historical instances through market research and statistics.

[0059] It should also be noted that in a certain historical breach of contract, the product supply and demand ratio and price composition data pair at the time of the breach are expressed in the form of (product supply and demand ratio, price). Each data pair is obtained in this way.

[0060] If the affected supplier breaches its contract with a company during the product supply process, then that company is the company whose contract was breached.

[0061] By comparing the product supply and demand ratios of each data pair, data pairs with the same product supply and demand ratios are grouped together. Within each group, the price and corresponding probability of breach of contract for each data pair are plotted on a graph. This graph is used to obtain the relationship between the probability of breach of contract and the price under the corresponding product supply and demand ratio in that group. This method is used to obtain the relationship between the probability of breach of contract and the price under different product supply and demand ratios, and this relationship is used as the calculation relationship between the probability of breach of contract of the affected supplier and the enterprise's product supply and demand ratio and price.

[0062] It should be noted that in this graph, the x-axis represents price and the y-axis represents the probability of default.

[0063] It should also be noted that the calculation relationship between the probability of default and the price is obtained through a one-dimensional convolutional neural network. One-dimensional convolutional neural networks are existing technologies. The specific process is as follows: The curve is standardized, and a one-dimensional convolutional neural network is constructed with an input layer, a one-dimensional convolutional layer, an activation function layer, a one-dimensional pooling layer, a batch normalization layer, a Dropout layer, a fully connected layer, and an output layer. The network is then trained. After training, the processed curve is input into the one-dimensional convolutional neural network, and the calculated relationship between the probability of default and the price in the curve is output.

[0064] The risk warning module is used to issue an early warning when the enterprise's supply chain risk is high.

[0065] The database is used to store supply chain information, the production capacity of each industry in different historical time periods, the total production capacity of each industry in the previous time period, the reasons for each supplier's failure to meet the supply standards when supplying products to the company in previous periods and the supply situation to the company, as well as information on each supplier's breach of contract in previous periods and the highest product price that the company can offer to each supplier.

[0066] This invention identifies the industries in which a company's supply chain operates and obtains the related industries of each industry. Based on the historical capacity changes of each related industry and the current capacity changes of each related industry, it determines whether the industries in which the supply chain operates are negatively impacted by other industries. If they are not negatively impacted by other industries, it determines whether the company's supply chain risk is high based on the supply relationships and supply situations of each supplier and other end-user companies. If they are negatively impacted by other industries, it determines whether the company's supply chain risk is high based on the probability of each supplier defaulting on contracts, thus ensuring the accuracy and timeliness of supply chain identification.

[0067] The examples described in this invention are not limited to the specific embodiments listed above. The examples are merely illustrative to facilitate understanding of the invention and do not constitute a limitation on the scope of protection of this invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of this invention should be included within the scope of protection.

[0068] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent supply chain risk early warning system based on multi-source data fusion, characterized in that, Includes the following modules: The data acquisition module is used to retrieve the company's supply chain information from the database; The supply chain analysis module is used to obtain the supply relationships of each supplier and other end enterprises of each supplier from the enterprise's supply chain information, as well as the current production capacity of other industries, analyze the impact of other industries on the enterprise's supply chain, obtain the product demand of the enterprise and other end enterprises of each supplier, and analyze whether the enterprise's supply chain is risky. The risk warning module is used to issue warnings when the company's supply chain risks are high; The database is used to store supply chain information, the production capacity of each industry in different historical time periods, the total production capacity of each industry in the previous time period, the reasons for each supplier's failure to meet the supply standards when supplying products to the company in previous periods and the supply status of the company, as well as information on each supplier's breach of contract in previous periods and the highest product price that the company can offer to each supplier. 2.The intelligent supply chain risk early warning system based on multi-source data fusion of claim 1, wherein, The supply chain analysis module includes an industry impact analysis unit and a risk monitoring unit; The industry impact analysis unit is used to obtain the industries included in the enterprise's supply chain, refer to the industries in the market other than those included in the supply chain as other industries, select related industries from other industries, and determine whether the related industries have a negative impact on the enterprise's supply chain based on the current production capacity of each related industry. The risk monitoring unit is used to analyze whether the risk of the enterprise's supply chain is too high when the related industries do not have a negative impact on the enterprise's supply chain, based on the supply data of each supplier, the product demand of each marking terminal enterprise and the enterprise itself; and when the related industries have an impact on the enterprise's supply chain, it analyzes whether the risk of the enterprise's supply chain is high based on the impact of the related industries. 3.The intelligent supply chain risk early warning system based on multi-source data fusion of claim 2, characterized in that, The specific process for selecting related industries from other industries is as follows: Other industries are referred to as the industries to be analyzed, and the industries included in the enterprise's supply chain are referred to as the marked industries. The products of the marked industries and the industries to be analyzed, as well as the product flow of the industries to be analyzed, are obtained. The selection criteria for related industries are: (1) If the products of a certain industry to be analyzed are competing products with the products of a certain marked industry, then the industry to be analyzed is a related industry; (2) If the product flow of a certain industry to be analyzed includes a certain marked industry, then the industry to be analyzed is a related industry; When a certain industry to be analyzed meets any one of the selection criteria for related industries, the industry to be analyzed is a related industry. The related industries are selected in this way.

4. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 2, characterized in that, The specific process for determining whether related industries have a negative impact on the company's supply chain is as follows: The capacity of each related industry and each marked industry in the database is obtained at different historical time periods and plotted on a curve graph and marked with different colors. Based on the capacity changes of each related industry in the curve graph, the capacity increment of the related industry is calculated. Similarly, the capacity increment of the marked industry is calculated. The capacity increment includes 1 and -1. When the capacity increment of the related industry is the same as the capacity increment of the marked industry, it means that the capacity of each marked industry is positively correlated with the capacity of each related industry. Conversely, it means that they are negatively correlated. The database is used to obtain the total capacity of each related industry in the previous period and the total capacity of each related industry at present. The capacity increment of the current related industry is determined. Based on the capacity increment of the current related industry and the relationship between the capacity of each marked industry and the capacity of each related industry, the industry impact value is determined. If the industry impact value is 1, it means that each related industry has a negative impact on the enterprise's supply chain. If the industry impact value is 0, it means that each related industry has no negative impact on the enterprise's supply chain.

5. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 4, characterized in that, The specific process for determining the industry impact value is as follows: If the current capacity increment of the related industries is 1, and the capacity of each marked industry is positively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry has increased, and the industry shock value is 0. If the current capacity increment of the related industries is 1, and the capacity of each marked industry is negatively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry decreases, and the industry shock value is 1. If the current capacity increment of related industries is -1, and the capacity of each marked industry is positively correlated with the capacity of each related industry, then it means that the total capacity value of each marked industry decreases, and the industry shock value is 1. If the current capacity increment of related industries is -1, and the capacity of each marked industry is negatively correlated with the capacity of each related industry, it means that the total capacity value of each marked industry has increased, and the industry shock value is 0.

6. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 2, characterized in that, When related industries do not negatively impact a company's supply chain, the process for determining the risk level of that company's supply chain is as follows: A11. Obtain product supply data from each supplier to each marked terminal enterprise and the enterprise itself, as well as the product demand of each marked terminal enterprise and the enterprise itself. Determine whether the product supply meets the standards. When it meets the standards, it means that the enterprise's supply chain risk is small. When it does not meet the standards, the suppliers whose product supply does not meet the standards are called each marked supplier. Obtain the reasons for the non-compliance of each marked supplier and the objects of the non-compliance of product supply. A12. If one or more marked suppliers fail to meet the requirements and include the enterprise, it indicates that the enterprise has a high supply chain risk. Conversely, based on the reasons for the failure of each marked supplier to meet the requirements, analyze whether the supply of products from each marked supplier to its respective marked end enterprise will affect the supply of products to the enterprise. If it will affect the supply, it indicates that the enterprise has a high supply chain risk. Conversely, it indicates that the enterprise has a low supply chain risk.

7. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 6, characterized in that, The analysis of whether the product supply of each marking supplier to its respective marking terminal enterprise will affect the product supply to that enterprise is as follows: For a given supplier, the reasons for non-compliance in each of the supplier's historical product supply to the enterprise are retrieved from the database. Based on the reasons for non-compliance, similar historical supply events are determined. The supply situation of the supplier to the enterprise during each similar historical supply event is retrieved from the database. If the supply situation of the supplier to the enterprise is good during each similar historical supply event, it means that the supplier's product supply to its various marked end enterprises will not affect the supply to the enterprise. Conversely, it means that the supplier's product supply to its various marked end enterprises will affect the supply to the enterprise. This method is used to determine whether the product supply of each marking supplier to its respective marking terminal enterprise will affect the product supply to that enterprise.

8. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 2, characterized in that, When related industries negatively impact a company's supply chain, the process for assessing the risk level of that supply chain is as follows: A21. Each supplier negatively impacted is referred to as an affected supplier. Obtain the mark-end enterprise of each affected supplier and the enterprise's product supply demand for each affected supplier. A22. Based on the terminal enterprises of each affected supplier and the supply demand of each enterprise for the products of each affected supplier, determine whether the probability of each affected supplier defaulting on the contract is high. If there are affected suppliers with a high probability of defaulting on the contract, it means that the enterprise has a high supply chain risk. Conversely, if there are no affected suppliers with a high probability of defaulting on the contract, it means that the enterprise has a low supply chain risk.

9. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 8, characterized in that, The specific process for determining whether each affected supplier is likely to breach the contract is as follows: In a certain affected supplier, A31, obtain the product supply demand of each marked terminal enterprise of the affected supplier and the product supply demand of each enterprise to the affected supplier, calculate the proportion of the enterprise's product supply demand, and obtain the information of each historical breach of contract of the affected supplier from the database, and analyze the calculation relationship between the probability of breach of contract of the affected supplier and the proportion of the enterprise's product supply demand and the price. A32. Obtain the highest product price that the company can offer to this supplier from the database. Based on the company's product supply demand ratio, the highest product price that can be offered, and the calculation relationship obtained in step A31, obtain the probability of the affected supplier defaulting on the contract. Compare this probability with a preset default probability threshold. If the probability is greater than the preset default probability threshold, it means that the affected supplier has a high probability of defaulting on the contract. Conversely, if the probability is lower, it means that the affected supplier has a low probability of defaulting on the contract. Use this method to determine whether the probability of each affected supplier defaulting on the contract is high.

10. The intelligent supply chain risk early warning system based on multi-source data fusion according to claim 9, characterized in that, The specific process for analyzing the probability of breach of contract by the affected supplier, the proportion of the enterprise's product supply demand, and the price is as follows: Obtain the percentage of product supply demand, price, and probability of breach of contract of the affected supplier in each of the historical breaches of contract, and construct data pairs, which consist of the percentage of product supply demand and price. By comparing the product supply and demand ratios of each data pair, data pairs with the same product supply and demand ratios are grouped together. Within each group, the price and corresponding probability of breach of contract for each data pair are plotted on a graph. This graph is used to obtain the relationship between the probability of breach of contract and the price under the corresponding product supply and demand ratio in that group. This method is used to obtain the relationship between the probability of breach of contract and the price under different product supply and demand ratios, and this relationship is used as the calculation relationship between the probability of breach of contract of the affected supplier and the enterprise's product supply and demand ratio and price.

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