Title
Similarity Measures, Penalty Functions, And Fuzzy Entropy From New Fuzzy Subsethood Measures
Abstract
In this study, we discuss a new class of fuzzy subsethood measures between fuzzy sets. We propose a new definition of fuzzy subsethood measure as an intersection of other axiomatizations and provide two construction methods to obtain them. The advantage of this new approach is that we can construct fuzzy subsethood measures by aggregating fuzzy implication operators which may satisfy some properties widely studied in literature. We also obtain some of the classical measures such as the one defined by Goguen. The relationships with fuzzy distances, penalty functions, and similarity measures are also investigated. Finally, we provide an illustrative example which makes use of a fuzzy entropy defined by means of our fuzzy subsethood measures for choosing the best fuzzy technique for a specific problem.
Year
DOI
Venue
2019
10.1002/int.22096
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
DocType
Volume
fuzzy entropy, fuzzy sets, penalty functions, similarity measures, subsethood measure
Journal
34
Issue
ISSN
Citations 
6
0884-8173
1
PageRank 
References 
Authors
0.37
0
8