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
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;
Conference_Titel :
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4673-0458-0
DOI :
10.1109/CDCIEM.2012.201
