Hybrid robust approach for TSK fuzzy modeling with outliers

This study proposes a hybrid robust approach for constructing Takagi–Sugeno–Kang (TSK) fuzzy models with outliers. The approach consists of a robust fuzzy C-regression model (RFCRM) clustering algorithm in the coarse-tuning phase and an annealing robust back-propagation (ARBP) learning algorithm in...

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Veröffentlicht in:	Expert systems with applications Jg. 36; H. 5; S. 8925 - 8931
Hauptverfasser:	Chuang, Chen-Chia, Jeng, Jin-Tsong, Tao, Chin-Wang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2009
Schlagworte:	Hybrid robust approach Outliers Robust clustering algorithm Robust learning algorithm TSK fuzzy model Outliers Robust learning algorithm TSK fuzzy model Hybrid robust approach Robust clustering algorithm
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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