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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning

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Multi-Objective Optimization using Artificial Intelligence Techniques (Paperback, 1st ed. 2020) Loot Price: R1,747
Discovery Miles 17 470
Repayment Terms: R164 pm x 12*
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Multi-Objective Optimization using Artificial Intelligence Techniques (Paperback, 1st ed. 2020): Seyed Ali Mirjalili, Jin Song...

Multi-Objective Optimization using Artificial Intelligence Techniques (Paperback, 1st ed. 2020)

Seyed Ali Mirjalili, Jin Song Dong

Series: SpringerBriefs in Applied Sciences and Technology

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Loot Price R1,747 Discovery Miles 17 470 | Repayment Terms: R164 pm x 12*

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This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: SpringerBriefs in Applied Sciences and Technology
Release date: July 2019
First published: 2020
Authors: Seyed Ali Mirjalili • Jin Song Dong
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 58
Edition: 1st ed. 2020
ISBN-13: 978-3-03-024834-5
Categories: Books > Business & Economics > Business & management > Management & management techniques > Operational research
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 3-03-024834-8
Barcode: 9783030248345

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