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Nature-inspired computing and optimi...

Nakamatsu, Kazumi.

Nature-inspired computing and optimizationtheory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nature-inspired computing and optimizationedited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu.
Reminder of title:	theory and applications /
other author:	Patnaik, Srikanta.
Published:	Cham :Springer International Publishing :2017.
Description:	xxi, 494 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Natural computation.
Online resource:	http://dx.doi.org/10.1007/978-3-319-50920-4
ISBN:	9783319509204$q(electronic bk.)

Nature-inspired computing and optimizationtheory and applications /
Nature-inspired computing and optimizationtheory and applications /[electronic resource] :edited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu. - Cham :Springer International Publishing :2017. - xxi, 494 p. :ill. (some col.), digital ;24 cm. - Modeling and optimization in science and technologies,v.102196-7326 ;. - Modeling and optimization in science and technologies ;v.2..

From the content: The Nature of Nature: Why Nature Inspired Algorithms Work -- Improved Bat Algorithm in Noise-Free and Noisy Environments -- Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.le.

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

ISBN: 9783319509204$q(electronic bk.)

Standard No.: 10.1007/978-3-319-50920-4doiSubjects--Topical Terms:

339160
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Nature-inspired computing and optimizationtheory and applications /
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245 0 0 $a Nature-inspired computing and optimization $h [electronic resource] : $b theory and applications / $c edited by Srikanta Patnaik, Xin-She Yang, Kazumi Nakamatsu.
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490 1 $a Modeling and optimization in science and technologies, $x 2196-7326 ; $v v.10
505 0 $a From the content: The Nature of Nature: Why Nature Inspired Algorithms Work -- Improved Bat Algorithm in Noise-Free and Noisy Environments -- Multi-objective Ant Colony Optimisation in Wireless Sensor Networks.le.
520 $a The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.
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700 1 $a Patnaik, Srikanta. $3 278789
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700 1 $a Nakamatsu, Kazumi. $3 348479
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