Generalized hesitant fuzzy knowledge measure with its application to multi-criteria decision-making

被引:9
作者
Singh, Surender [1 ]
Ganie, Abdul Haseeb [1 ]
机构
[1] Shri Mata Vaishno Devi Univ, Fac Sci, Sch Math, Katra 182320, Jammu & Kashmir, India
关键词
Hesitant fuzzy set (HFS); Multi-criteria decision-making; Hesitant fuzzy entropy measure; Hesitant fuzzy knowledge measure; INFORMATION MEASURES; SIMILARITY MEASURES; ENTROPY MEASURES; SETS; DISTANCE; SYSTEMS;
D O I
10.1007/s41066-021-00263-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hesitant fuzzy (HF) entropy and HF-knowledge measures are two dual concepts that have similar practical applications despite different mathematical structures. In some real-life scenarios, one particular entropy/knowledge measure may not be reasonable due to some undesirable and counter-intuitive situations. In this paper, we introduce a one-parametric generalized knowledge measure in the HF-setting. Such a generalization provides a class of HF-knowledge measures and hence the flexibility in the practical problems. We show the advantages of the generalized measure over the existing HF-entropy/knowledge measures in view of weight computation in the decision-making problems and ambiguity computation of two different hesitant fuzzy elements. At last, we apply the proposed generalized knowledge measure of HFSs in multi-criteria decision-making (MCDM) using the bidirectional projection method in the hesitant fuzzy environment.
引用
收藏
页码:239 / 252
页数:14
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