摘要
随着全球气温普遍升高和极端气候事件的增多,各国的环境保护意识逐渐增强。在这种情况下,新能源汽车行业成为改善环境气候的重要领域之一。拟从供应链金融角度出发,结合KNN模型与SVM模型的优点,提出了KNN-SVM组合模型,并首次将其应用于新能源汽车行业相关企业信用风险评估中。结果发现,相比Logistic模型、KNN模型以及SVM模型,KNN-SVM组合模型具有更好的评估效果。
With the general rise in global temperatures and the increase in extreme weather events,countries have gradually strengthened their awareness of environmental protection.In this context,the new energy vehicle industry has become an important field for improving the environmental climate.From the perspective of supply chain finance,this article proposes a KNN-SVM combined model by combining the advantages of the KNN model and SVM model,which is applied for the first time in credit risk assessment of relevant enterprises in the new energy vehicle industry.The results show that compared with the Logistic model,KNN model and SVM model,the KNN-SVM combined model has better evaluation performance.
作者
刘千
武家旭
Liu Qian;Wu Jiaxu(School of Finance,Harbin University of Commerce,Harbin,Heilongjiang 150028,China)
出处
《黑龙江工业学院学报(综合版)》
2023年第9期44-50,共7页
Journal of Heilongjiang University of Technology(Comprehensive Edition)
基金
哈尔滨商业大学青年创新人才支持计划(项目编号:2020CX14)。
关键词
支持向量机
K近邻算法
供应链金融
信用风险
新能源汽车行业
support vector machine
K-Nearest Neighbor Algorithm
supply chain finance
credit risk
new energy vehicle industry