面向横截面数据的级差最大化灰色指标关联决策模型  

Grey Incidence Decision-Making Model Based on Level Difference Maximization for Cross-Sectional Data

作　　者：余鹏 马珩[1] 李瑞雪 周福礼 Yu Peng;Ma Heng;Li Ruixue;Zhou Fuli(School of Economics and Management,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;School of Economics and Management,Zhengzhou University of Light Industry,Zhengzhou 450001,China)

机构地区：[1]南京航空航天大学经济与管理学院,南京211106 [2]郑州轻工业大学经济与管理学院,郑州450001

出　　处：《统计与决策》2020年第8期160-164,共5页Statistics & Decision

基　　金：国家社会科学基金资助项目(19BJL052)。

摘　　要：针对现有横截面数据灰色关联模型中指标的排序变换影响关联结果的问题,文章从距离的接近性角度,以指数函数的形式表征关联系数;借助TOPSIS思想,并利用级差最大化组合赋权原理分别从正、负理想两个角度对指标进行赋权,集成一种面向横截面数据的级差最大化灰色指标关联决策模型,并对该模型的规范性等性质进行证明。通过实例验证该方法不受指标排序的影响。Aiming at the problem that the order of indicators in cross-sectional data affects grey incidence results,this paper presents the correlation coefficient in the form of exponential function from the perspective of proximity in distance.And then,with the help of TOPSIS thought,the paper uses the principle of level difference maximization combined weighting to assign weights to indicators from the two dimensions of positive and negative ideal,respectively,and then integrates a grey index relational decision-making model of grade-difference maximization for cross section data.Finally,the paper proves the normativity and other properties of the model.Through examples analysis,the paper verifies that the proposed model is not affected by index ordering.

关 键 词：横截面数据 级差最大化 指数函数 灰色关联分析 

分 类 号：N941.5[自然科学总论—系统科学]