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Evolutionary Computation Techniques: A Comparative Perspective (Paperback, Softcover reprint of the original 1st ed. 2017) Loot Price: R3,020
Discovery Miles 30 200
Evolutionary Computation Techniques: A Comparative Perspective (Paperback, Softcover reprint of the original 1st ed. 2017):...

Evolutionary Computation Techniques: A Comparative Perspective (Paperback, Softcover reprint of the original 1st ed. 2017)

Erik Cuevas, Valentin Osuna, Diego Oliva

Series: Studies in Computational Intelligence, 686

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Loot Price R3,020 Discovery Miles 30 200 | Repayment Terms: R283 pm x 12*

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This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Studies in Computational Intelligence, 686
Release date: July 2018
First published: 2017
Authors: Erik Cuevas • Valentin Osuna • Diego Oliva
Dimensions: 235 x 155 x 13mm (L x W x T)
Format: Paperback
Pages: 222
Edition: Softcover reprint of the original 1st ed. 2017
ISBN-13: 978-3-319-84568-5
Categories: Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 3-319-84568-3
Barcode: 9783319845685

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