{"title":"基于数值分析算法的供应链金融风险评估分析","authors":"Na Li, Hao Dong","doi":"10.17993/3cemp.2023.120252.217-234","DOIUrl":null,"url":null,"abstract":"To promote the coordination and stability of supply chain finance and improve the financing environment of small and medium-sized enterprises, this paper designs a supply chain finance risk assessment and analysis platform. Combining the characteristics of a large amount of risk assessment data, a numerical analysis algorithm is introduced in the process of platform design, and the extrapolation method in the numerical analysis algorithm is used to calculate the risk assessment- related data. To make the calculation faster and the data more accurate, the central difference quotient extrapolation is used to accelerate and a downtime mechanism is introduced. Firstly, the approximation formula for the calculation is constructed, followed by the construction of a sequence of variable steps to obtain a sequence of approximations. Finally, the obtained approximate sequence values are used to construct an interpolating polynomial, and the constant term of the polynomial, which is the final risk factor, is obtained through continuous iteration. To verify the effectiveness of the numerical analysis-based algorithm in supply chain financial risk assessment, the simulation results show that the risk assessment accuracy of the numerical analysis-based supply chain financial risk assessment platform is as high as 99% and the time required is 17 seconds higher than other assessment models, which verifies that the numerical analysis algorithm can improve the accuracy and rapidity of risk assessment.","PeriodicalId":40997,"journal":{"name":"3C Empresa","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of supply chain finance risk assessment based on numerical analysis algorithm\",\"authors\":\"Na Li, Hao Dong\",\"doi\":\"10.17993/3cemp.2023.120252.217-234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To promote the coordination and stability of supply chain finance and improve the financing environment of small and medium-sized enterprises, this paper designs a supply chain finance risk assessment and analysis platform. Combining the characteristics of a large amount of risk assessment data, a numerical analysis algorithm is introduced in the process of platform design, and the extrapolation method in the numerical analysis algorithm is used to calculate the risk assessment- related data. To make the calculation faster and the data more accurate, the central difference quotient extrapolation is used to accelerate and a downtime mechanism is introduced. Firstly, the approximation formula for the calculation is constructed, followed by the construction of a sequence of variable steps to obtain a sequence of approximations. Finally, the obtained approximate sequence values are used to construct an interpolating polynomial, and the constant term of the polynomial, which is the final risk factor, is obtained through continuous iteration. To verify the effectiveness of the numerical analysis-based algorithm in supply chain financial risk assessment, the simulation results show that the risk assessment accuracy of the numerical analysis-based supply chain financial risk assessment platform is as high as 99% and the time required is 17 seconds higher than other assessment models, which verifies that the numerical analysis algorithm can improve the accuracy and rapidity of risk assessment.\",\"PeriodicalId\":40997,\"journal\":{\"name\":\"3C Empresa\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3C Empresa\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17993/3cemp.2023.120252.217-234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3C Empresa","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17993/3cemp.2023.120252.217-234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS","Score":null,"Total":0}
Analysis of supply chain finance risk assessment based on numerical analysis algorithm
To promote the coordination and stability of supply chain finance and improve the financing environment of small and medium-sized enterprises, this paper designs a supply chain finance risk assessment and analysis platform. Combining the characteristics of a large amount of risk assessment data, a numerical analysis algorithm is introduced in the process of platform design, and the extrapolation method in the numerical analysis algorithm is used to calculate the risk assessment- related data. To make the calculation faster and the data more accurate, the central difference quotient extrapolation is used to accelerate and a downtime mechanism is introduced. Firstly, the approximation formula for the calculation is constructed, followed by the construction of a sequence of variable steps to obtain a sequence of approximations. Finally, the obtained approximate sequence values are used to construct an interpolating polynomial, and the constant term of the polynomial, which is the final risk factor, is obtained through continuous iteration. To verify the effectiveness of the numerical analysis-based algorithm in supply chain financial risk assessment, the simulation results show that the risk assessment accuracy of the numerical analysis-based supply chain financial risk assessment platform is as high as 99% and the time required is 17 seconds higher than other assessment models, which verifies that the numerical analysis algorithm can improve the accuracy and rapidity of risk assessment.