Improving Wang–Mendel method performance in fuzzy rules generation using the fuzzy C-means clustering algorithm

The generation of fuzzy rules from samples for fuzzy modeling and control is significant. If samples contain noise and outliers, the Wang–Mendel (WM) method may lead to the extraction of invalid rules resulting in low confidence of the rules. The scale of the samples also affects the efficiency of t...

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Bibliographic Details
Published in:	Neurocomputing (Amsterdam) Vol. 151; pp. 1293 - 1304
Main Authors:	Gou, Jin, Hou, Feng, Chen, Wenyu, Wang, Cheng, Luo, Wei
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 03.03.2015
Subjects:	Algorithms Clustering Completeness Construction Fuzzy Fuzzy C-means clustering algorithm Fuzzy logic Fuzzy set theory Fuzzy system Mathematical models Robustness Wang–Mendel method Fuzzy C-means clustering algorithm Fuzzy system Robustness Wang–Mendel method Completeness
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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