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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Vydané v:	Applied intelligence (Dordrecht, Netherlands) Ročník 36; číslo 2; s. 454 - 471
Hlavní autori:	Lin, Sheng-Fuu, Chang, Jyun-Wei, Hsu, Yung-Chi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.03.2012 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
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