Knowledge measure of hesitant fuzzy set and its application in multi-attribute decision-making

被引:28
作者
Lalotra, Sumita [1 ]
Singh, Surender [1 ]
机构
[1] Shri Mata Vaishno Devi Univ, Sch Math, Katra 182320, Jammu & Kashmir, India
关键词
Hesitant fuzzy set (HFS); Hesitant fuzzy entropy; Hesitant fuzzy knowledge measure; MADM; PROGRAMMING APPROACH; PREFERENCE RELATIONS; ENTROPY MEASURES; MATRIX GAMES; PAYOFFS;
D O I
10.1007/s40314-020-1095-y
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The fuzzy knowledge measure is considered as a dual measure of fuzzy entropy. In this work, we introduce an axiomatic framework to define a hesitant fuzzy knowledge measure (HF-knowledge measure) and investigate hesitant fuzzy entropy (HF-entropy) and HF-knowledge measure from the viewpoint of duality. We provide a characterization result to obtain a class of the HF-knowledge measure. We also obtain an HF-knowledge measure from similarity and dissimilarity measures of hesitant fuzzy sets. Here, we introduce an HF-knowledge measure and show its effectiveness with the help of an illustrative example from the viewpoint of linguistic hedges. We apply the proposed HF-knowledge measure to multiple-attribute decision-making (MADM) problem by utilizing the TOPSIS method and justify its advantage over existing HF-entropies.
引用
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页数:31
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