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Nature-inspired optimizerstheories, ...
~
Lewis, Andrew.
Nature-inspired optimizerstheories, literature reviews and applications /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Nature-inspired optimizersedited by Seyedali Mirjalili, Jin Song Dong, Andrew Lewis.
其他題名:
theories, literature reviews and applications /
其他作者:
Mirjalili, Seyedali.
出版者:
Cham :Springer International Publishing :2020.
面頁冊數:
xvi, 238 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer eBooks
標題:
Evolutionary computation.
電子資源:
https://doi.org/10.1007/978-3-030-12127-3
ISBN:
9783030121273$q(electronic bk.)
Nature-inspired optimizerstheories, literature reviews and applications /
Nature-inspired optimizers
theories, literature reviews and applications /[electronic resource] :edited by Seyedali Mirjalili, Jin Song Dong, Andrew Lewis. - Cham :Springer International Publishing :2020. - xvi, 238 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8111860-949X ;. - Studies in computational intelligence ;v. 216..
Preface -- Chapter 1. Introduction to Nature-inspired Algorithms -- Chapter 2. Ant Colony Optimizer: Theory, Literature Review, and Application in AUV Path Planning -- Chapter 3. Ant Lion Optimizer: Theory, Literature Review, and Application in Multi-layer Perceptron Neural Network -- Chapter 4. Dragonfly Algorithm: Theory, Literature Review, and Application in Feature Selection -- Chapter 5. Genetic Algorithm: Theory, Literature Review, and Application in Image Reconstruction etc.
This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.
ISBN: 9783030121273$q(electronic bk.)
Standard No.: 10.1007/978-3-030-12127-3doiSubjects--Topical Terms:
231709
Evolutionary computation.
LC Class. No.: TA347.E96 / N388 2020
Dewey Class. No.: 006.3823
Nature-inspired optimizerstheories, literature reviews and applications /
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