A self-organization mining based hybrid evolution learning for TSK-type fuzzy model design

In this paper, a self-organization mining based hybrid evolution (SOME) learning algorithm for designing a TSK-type fuzzy model (TFM) is proposed. In the proposed SOME, group-based symbiotic evolution (GSE) is adopted in which each group in the GSE represents a collection of only one fuzzy rule. The...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Jg. 36; H. 2; S. 454 - 471
Hauptverfasser:	Lin, Sheng-Fuu, Chang, Jyun-Wei, Hsu, Yung-Chi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.03.2012 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Chromosomes Computer Science Controllers Data mining Evolution Fuzzy Fuzzy logic Fuzzy set theory Fuzzy sets Genetic algorithms Learning Machines Manufacturing Mechanical Engineering Mutation Network topologies Optimization techniques Processes Strategy Identification Data mining Genetic algorithm Fuzzy model FP-Growth Group-based symbiotic evolution
ISSN:	0924-669X, 1573-7497
Online-Zugang:	Volltext
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