Paper Info
Title
Similarity measures of interval-valued fuzzy sets.
Abstract
Interval-valued fuzzy set (briefly, IVFS) is a generalization of fuzzy set that may better model imperfect information. Similarity measure is a useful tool for determining the similarity degree between two fuzzy concepts. In this paper, the definition of similarity measure of IVFSs is presented. Three approaches to constructing similarity measures of IVFSs are proposed. Based on the approaches, three computation formulae for calculating the similarity degree between IVFSs are obtained. The properties of similarity measures of IVFSs are examined as a whole.
Year
DOI
Venue
2015
10.3233/IFS-141492
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Interval-valued fuzzy set,fuzzy set,similarity measure,fuzzy equivalence
Fuzzy clustering,Fuzzy classification,Fuzzy measure theory,Fuzzy set,Jaccard index,Artificial intelligence,Membership function,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
28
5
1064-1246
Citations 
PageRank 
References 
2
0.40
15
Authors
4
Name
Order
Citations
PageRank
Yingfang Li1687.41
Keyun Qin248039.80
Xingxing He38413.90
Dan Meng447667.10