Typical Characteristic-Based Type-2 Fuzzy C-Means Algorithm

Type-2 fuzzy sets provide an efficient vehicle for handling uncertainties of real-world problems, including noisy observations. Bringing type-2 fuzzy sets to clustering algorithms offers more flexibility to handle uncertainties associated with membership concepts caused by a noisy environment. Howev...

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Veröffentlicht in:	IEEE transactions on fuzzy systems Jg. 29; H. 5; S. 1173 - 1187
Hauptverfasser:	Yang, Xiyang, Yu, Fusheng, Pedrycz, Witold
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Cardinality center of gravity (COG) characteristics Clustering Clustering algorithms fuzzy clustering Fuzzy sets Linear programming Noise measurement Partitioning algorithms Phase change materials type-2 fuzzy sets (T2FS) Uncertainty
ISSN:	1063-6706, 1941-0034
Online-Zugang:	Volltext
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