Paper Info
Title
Novel fuzzy information proximity measures
Abstract
As a measure of information shared between two fuzzy pattern vectors, the fuzzy information proximity measure (FIPM) plays an important part in fuzzy pattern recognition, fuzzy clustering analysis and fuzzy approximate reasoning. In this paper, two novel FIPMs are set up. Firstly, an axiom theory about the FIPM is given, and different expressions of the FIPM are discussed. A new FIPM is then proposed based on the axiom theory of the FIPM and the concept of fuzzy subsethood function. Two concepts based on the idea of Shannon information entropy, fuzzy joint entropy (FJE) and fuzzy conditional entropy (FCE), are proposed and the basic properties of FJE and FCE are given and proved. Finally, classical similarity measures such as dissimilarity measure (DM) and similarity measure (SM) are studied, and two new measures, fuzzy absolute information measure (FAIM) and fuzzy relative information measure (FRIM), are set up, which can be used as measures of the proximity between fuzzy sets A and B.
Year
DOI
Venue
2007
10.1177/0165551507076332
J. Information Science
Keywords
DocType
Volume
fuzzy pattern vector,fuzzy relative information measure,fuzzy set,fuzzy information proximity measure fipm,fuzzy absolute information measure faim,novel fuzzy information proximity,fuzzy relative information measure frim,fuzzy nearness degree,fuzzy joint entropy fje,fuzzy joint entropy,fuzzy absolute information measure,fuzzy approximate reasoning,fuzzy conditional entropy,fuzzy conditional entropy fce,fuzzy pattern recognition,fuzzy information proximity measure,fuzzy clustering analysis
Journal
33
Issue
ISSN
Citations 
6
0165-5515
6
PageRank 
References 
Authors
0.58
7
4
Name
Order
Citations
PageRank
Shifei Ding1107494.63
Shixiong Xia210213.28
Fengxiang Jin312410.72
Zhongzhi Shi42440238.03