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Nature-Inspired Optimizers - Theories, Literature Reviews and Applications (Paperback, 1st ed. 2020) Loot Price: R2,789
Discovery Miles 27 890
Nature-Inspired Optimizers - Theories, Literature Reviews and Applications (Paperback, 1st ed. 2020): Seyed Ali Mirjalili, Jin...

Nature-Inspired Optimizers - Theories, Literature Reviews and Applications (Paperback, 1st ed. 2020)

Seyed Ali Mirjalili, Jin Song Dong, Andrew Lewis

Series: Studies in Computational Intelligence, 811

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Loot Price R2,789 Discovery Miles 27 890 | Repayment Terms: R261 pm x 12*

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This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Studies in Computational Intelligence, 811
Release date: October 2020
First published: 2020
Editors: Seyed Ali Mirjalili • Jin Song Dong • Andrew Lewis
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 238
Edition: 1st ed. 2020
ISBN-13: 978-3-03-012129-7
Categories: Books > Science & Mathematics > Mathematics > Optimization > General
Books > Computing & IT > Applications of computing > Artificial intelligence > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN: 3-03-012129-1
Barcode: 9783030121297

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