Nature-Inspired Design of Hybrid Intelligent Systems (Hardcover, 1st ed. 2017)

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book's third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 667
Release date:	December 2016
First published:	2017
Editors:	Patricia Melin • Oscar Castillo • Janusz Kacprzyk
Dimensions:	235 x 155 x 44mm (L x W x T)
Format:	Hardcover
Pages:	838
Edition:	1st ed. 2017
ISBN-13:	978-3-319-47053-5
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-47053-1
Barcode:	9783319470535

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