Exponential Jensen intuitionistic fuzzy divergence measure with applications in medical investigation and pattern recognition

被引：19

作者：

Joshi, Rajesh ^{[1
]}

Kumar, Satish ^{[1
]}

机构：

[1] Maharishi Markandeshwar Univ, Dept Math, Mullana 133207, Ambala, India

来源：

SOFT COMPUTING | 2019年 / 23卷 / 18期

基金：

英国科研创新办公室;

关键词：

Intuitionistic fuzzy set; Divergence measure; Intuitionistic fuzzy divergence measure; Medical diagnosis; Pattern recognition; ATTRIBUTE DECISION-MAKING; SIMILARITY MEASURES; SETS; ENTROPY; INFORMATION; DISTANCE;

D O I：

10.1007/s00500-018-3505-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The need of suitable divergence measures arises as they play an important role in the problems related to discrimination and inferences. This communication is intended to introduce one such exponential divergence measure based on well-known exponential entropy introduced by Pal and Pal and its validation. Further, this idea has been generalized to introduce a new exponential divergence measure for intuitionistic fuzzy sets. Besides establishing its validity, some of its major properties are also studied. In addition to this, applications of proposed divergence measure for IFSs are given in medical investigation and pattern recognition.

引用

页码：8995 / 9008

页数：14

共 47 条

[1]

[Anonymous], 2010, Intuitionistic Fuzzy Sets: Theory and Applications

[2] INTUITIONISTIC FUZZY-SETS [J].