General Type-2 Fuzzy C-Means Algorithm for Uncertain Fuzzy Clustering

Pattern recognition in real-world data is subject to various sources of uncertainty that should be appropriately managed. The focus of this paper is the management of uncertainty associated with parameters of fuzzy clustering algorithms. Type-2 fuzzy sets (T2 FSs) have received increased research in...

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Veröffentlicht in:	IEEE transactions on fuzzy systems Jg. 20; H. 5; S. 883 - 897
Hauptverfasser:	Linda, O., Manic, M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.10.2012 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Clustering algorithms Construction Frequency selective surfaces Fuzzy Fuzzy C-means Fuzzy logic Fuzzy set theory Fuzzy sets general type-2 fuzzy sets Linguistics Mathematical models Partitioning algorithms pattern recognition Pragmatics Studies Uncertainty α-planes representation
ISSN:	1063-6706, 1941-0034
Online-Zugang:	Volltext
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