Monotonic Similarity Measures of Interval-Valued Fuzzy Sets and Their Applications

被引：8
作者：
Deng, Guannan [1 ]
Song, Lianlian [1 ]
Jiang, Yanli [1 ]
Fu, Jingchao [1 ]
机构：
[1] Northeast Elect Power Univ, Coll Sci, Jilin 132012, Peoples R China
来源：
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2017年 / 25卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Interval-valued fuzzy sets; similarity measure; monotonicity; entropy; inclusion measure; INCLUSION MEASURE; DISTANCE; NUMBERS; ENTROPY;
D O I：
10.1142/S0218488517500222
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A similarity measure is a measure that indicates the degree of similarity between two objects. The purpose of this work is to investigate the monotonicity properties and applications of similarity measures on interval-valued fuzzy sets. Through analyzing the intuitions of similarities, three kinds of monotonic similarity measures are defined. Furthermore, their properties and relationships with entropy and inclusion measure are investigated and discussed. Finally, some applications of the proposed monotonic similarity measures, such as pattern recognition, medical recognition, and medical diagnosis are presented.
引用
收藏
页码：515 / 544
页数：30
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