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Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics = Theory and Applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics/ edited by Oscar Castillo, Patricia Melin.
Reminder of title:	Theory and Applications /
other author:	Castillo, Oscar.
Description:	VIII, 195 p. 98 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-10960-2
ISBN:	9783319109602

Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics = Theory and Applications /
Fuzzy Logic Augmentation of Nature-Inspired Optimization MetaheuristicsTheory and Applications /[electronic resource] :edited by Oscar Castillo, Patricia Melin. - 1st ed. 2015. - VIII, 195 p. 98 illus.online resource. - Studies in Computational Intelligence,5741860-949X ;. - Studies in Computational Intelligence,564.

This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.

ISBN: 9783319109602

Standard No.: 10.1007/978-3-319-10960-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics = Theory and Applications /
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