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Nature-Inspired Computation and Swarm Intelligence - Algorithms, Theory and Applications (Paperback) Loot Price: R3,265
Discovery Miles 32 650
Nature-Inspired Computation and Swarm Intelligence - Algorithms, Theory and Applications (Paperback): Xin-She Yang

Nature-Inspired Computation and Swarm Intelligence - Algorithms, Theory and Applications (Paperback)

Xin-She Yang

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Loot Price R3,265 Discovery Miles 32 650 | Repayment Terms: R306 pm x 12*

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Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.

General

Imprint: Academic Press Inc
Country of origin: United States
Release date: April 2020
First published: 2020
Editors: Xin-She Yang
Dimensions: 235 x 191mm (L x W)
Format: Paperback
Pages: 442
ISBN-13: 978-0-12-819714-1
Categories: Books > Computing & IT > Computer software packages > General
Books > Computing & IT > Applications of computing > Signal processing
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LSN: 0-12-819714-5
Barcode: 9780128197141

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