Exponential similarity measures for Pythagorean fuzzy sets and their applications to pattern recognition and decision-making process

被引：47
|
作者：
Xuan Thao Nguyen [1 ]
Van Dinh Nguyen [1 ]
Van Hanh Nguyen [1 ]
Garg, Harish [2 ]
机构：
[1] Vietnam Natl Univ Agr, Fac Informat Technol, Hanoi, Vietnam
[2] Thapar Inst Engn & Technol, Sch Math, Patiala 147004, Punjab, India
来源：
COMPLEX & INTELLIGENT SYSTEMS | 2019年 / 5卷 / 02期
关键词：
Pythagorean fuzzy sets; Similarity measures; Decision-making problems; Pattern recognition; Exponential functions; VAGUE SETS; AGGREGATION OPERATORS; OPERATIONAL LAWS; EXTENSION; TOPSIS; INDEX;
D O I：
10.1007/s40747-019-0105-4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A Pythagorean fuzzy set is one of the successful extensions of the intuitionistic fuzzy set to handle the uncertain and fuzzy information in a more wider way. In this paper, some new exponential similarity measures (SMs) for measuring the similarities between objects are proposed. For it, we used the exponential function for the membership and the non-membership degrees and hence defined some series of the SMs for PFSs. The various desirable properties and their relations are examined. Several counter-intuitive cases are given to show the effectiveness of the proposed measures with the existing SMs. Furthermore, examples to classify the pattern recognition and the decision-making problems are presented and compared with the existing approaches.
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页码：217 / 228
页数：12
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