New Fuzzy Similarity Measures: From Intuitionistic To Type-2 Fuzzy Sets

2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)(2017)

引用 5|浏览90
暂无评分
摘要
Fuzzy Similarity Measure (FSM) is one of the most used techniques for classification, pattern recognition or knowledge reduction. While many type-1 FSMs exist, few ones exist for type-2 fuzzy sets. In this paper, we introduce three similarity measures between Interval Type-2 Fuzzy Sets (IT-2 FSs) as an extension of some distance measures between Intuitionistic Fuzzy Sets (IFSs). Many definitions and properties are exposed in order to prove that the formulas presented are indeed similarity measures. Experimental results are presented, comparison with other existing type-2 FSMs is done and interpretation is given in order to satisfy FSM properties.
更多
查看译文
关键词
fuzzy similarity measures,intuitionistic fuzzy sets,classification,pattern recognition,knowledge reduction,Interval Type-2 Fuzzy Sets,IT-2 FS,distance measures,IFS,type-2 FSM
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要