DocumentCode
1681001
Title
T-Transitive Interval-Valued Fuzzy Relations for Clustering
Author
Wang, Ching-Nan ; Yang, Miin-Shen
Author_Institution
Dept. of Appl. Math., Chung Yuan Christian Univ., Chungli, Taiwan
fYear
2012
Firstpage
822
Lastpage
826
Abstract
Since interval-valued memberships is better than real membership values to represent higher-order imprecision and vagueness for human perception. In this paper, we extend fuzzy relations to interval-valued fuzzy relations and then construct T-transitive interval-valued fuzzy relations for clustering. We then apply the proposed method to a practical example.
Keywords
data analysis; fuzzy set theory; pattern clustering; T-transitive interval-valued fuzzy relations; clustering; data analysis; higher-order imprecision representation; human perception; interval-valued fuzzy sets; interval-valued memberships; vagueness representation; Clustering algorithms; Clustering methods; Cognition; Educational institutions; Fuzzy sets; Moment methods; Partitioning algorithms; Clustering; Fuzzy set; Interval-valued fuzzy relation; T-transitive fuzzy relation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location
Hunan
Print_ISBN
978-1-4673-0458-0
Type
conf
DOI
10.1109/CDCIEM.2012.201
Filename
6178608
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