基于毕达哥拉斯模糊集的大数据企业信用评价研究  

Research on Big Data Enterprise Credit Evaluation Based on Pythagoras Fuzzy Sets

作　　者：任杰 张红梅 REN Jie;ZHANG Hong-mei(School of Big Data Application and Economics(Guiyang University of Big Data Finance),Guizhou University of Finance and Economics,Guizhou 550025,China)

机构地区：[1]贵州财经大学大数据应用与经济学院(贵阳大数据金融学院),贵州贵阳550025

出　　处：《数学的实践与认识》2021年第14期64-77,共14页Mathematics in Practice and Theory

基　　金：贵州财经大学重点培育学科、急需学科方向专项课题《大数据企业的信用风险预测及评价研究》(2020ZJXK20)。

摘　　要：在已有的研究基础上提出了毕达哥拉斯模糊Frank交叉影响加权平均算子和毕达哥拉斯模糊Frank交叉影响加权几何算子并对其性质进行了相关推导和证明,最后以评估大数据企业信用风险为实例验证了该算子的有效性.结果表明:通过控制变量法,说明了引入交叉影响算子的重要性;通过引入Frank算子发现不同的η值会对记分函数值产生影响,但影响是较小的,该模型适用于对备选方案间差距较小的情形,而当备选方案间差距较大时该模型就会失灵.Based on the existing research,this paper puts forward the weighted average operator of Pythagorean fuzzy Frank cross influence and the weighted geometric operator of Pythagorean fuzzy Frank cross influence,and deduces and proves their properties.Finally,it takes the evaluation of big data enterprise credit risk as an example to verify the effectiveness of the operator.The results show that:through the control variable method,the importance of introducing the cross influence operator is explained;through the introduction of Frank operator,it is found that differentηvalues will have an impact on the score function value,but the impact is small,and the model is suitable for the case of small gap between alternatives,but when the gap between alternatives is large,the model will fail.

关 键 词：毕达哥拉斯模糊 Frank交叉影响算子 多属性群决策 

分 类 号：F49[经济管理—产业经济] O159[理学—数学]