A new measure of inaccuracy with its application to multi-criteria decision making under intuitionistic fuzzy environment

被引:51
|
作者
Verma, Rajkumar [1 ]
Sharma, Bhu Dev [1 ]
机构
[1] Deemed Univ, Jaypee Inst Informat Technol, Dept Math, Noida 201307, UP, India
关键词
Shannon's entropy; divergence measure; inaccuracy measure; fuzzy inaccuracy; intuitionistic fuzzy set; AGGREGATION OPERATORS; SIMILARITY MEASURES; SETS; ENTROPY; INFORMATION; NUMBERS;
D O I
10.3233/IFS-141148
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Mathematics has evolved to study vague phenomena that do not show statistical stability. Intuitionistic fuzzy sets best represent these vague phenomena, and admit set operations that do not arise otherwise, because of the functions involved in their definition. This has greatly enriched mathematics and has potential new directions for quantitative studies and applications. There is need to define quantitative measures for contents, vagueness, distance, etc. over intuitionistic fuzzy sets. In this paper a measure of inaccuracy between two 'intuitionistic fuzzy sets' is introduced and studied. The measure is demonstrated to satisfy some very interesting properties, which prepare ground for applications in multi-criteria decision making problems. We develop a method to solve multi-criteria decision making problems with the help of new measure. Finally, three numerical examples are given to illustrate the proposed method to solve multi-criteria decision-making problem under intuitionistic fuzzy environment.
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页码:1811 / 1824
页数:14
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