Evolutionary Algorithms and Neural Networks - Theory and Applications (Paperback, Softcover reprint of the original 1st ed. 2019)

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 780
Release date:	2019
First published:	2019
Authors:	Seyed Ali Mirjalili
Dimensions:	235 x 155 x 9mm (L x W x T)
Format:	Paperback
Pages:	156
Edition:	Softcover reprint of the original 1st ed. 2019
ISBN-13:	978-3-03-006572-0
Categories:	Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-006572-3
Barcode:	9783030065720

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