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Can lend chapters, not whole ebooks
Title
Nature-inspired optimizers : theories, literature reviews and applications / Seyedali Mirjalili, Jin Song Dong, Andrew Lewis, editors.
ISBN
9783030121273 (electronic book)
3030121275 (electronic book)
9783030121266
Published
Cham, Switzerland : Springer, 2020.
Language
English
Description
1 online resource (xvi, 238 pages) : illustrations.
Other Standard Identifiers
10.1007/978-3-030-12127-3 doi
10.1007/978-3-030-12
Call Number
TA347.E96
Dewey Decimal Classification
006.3/823
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed March 12, 2019).
Series
Studies in computational intelligence ; v. 811.
Preface
Chapter 1. Introduction to Nature-inspired Algorithms
Chapter 2. Ant Colony Optimizer: Theory, Literature Review, and Application in AUV Path Planning.-Chapter 3. Ant Lion Optimizer: Theory, Literature Review, and Application in Multi-layer Perceptron Neural Network
Chapter 4. Dragonfly Algorithm: Theory, Literature Review, and Application in Feature Selection
Chapter 5. Genetic Algorithm: Theory, Literature Review, and Application in Image Reconstruction etc.
