数学
偏爱
模糊逻辑
乘法函数
对数
模糊数
偏好关系
模糊集
统计
人工智能
计算机科学
数学分析
作者
Ying‐Ming Wang,Zhi‐Ping Fan
标识
DOI:10.1016/j.amc.2007.04.016
摘要
Logarithmic and geometric least squares methods (LLSM and GLSM) are, respectively, applied to deal with the group decision analysis problems with fuzzy preference relations, where multiplicative preference relations, if any, are transformed into fuzzy preference relations through proper transformation technique. Distance between any two fuzzy preference relations and the average distance from one fuzzy preference relation to all the others are defined and used to measure the relative importance of each fuzzy preference relation. A numerical example involving multiple fuzzy and multiplicative preference relations is examined using the proposed methods. It is shown that LLSM and GLSM provide two analytical and effective ways of modelling multiple fuzzy preference relations.
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