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Self-organizing migrating algorithmm...

Davendra, Donald.

Self-organizing migrating algorithmmethodology and implementation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Self-organizing migrating algorithmedited by Donald Davendra, Ivan Zelinka.
Reminder of title:	methodology and implementation /
other author:	Davendra, Donald.
Published:	Cham :Springer International Publishing :2016.
Description:	xviii, 289 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Evolutionary computation.
Online resource:	http://dx.doi.org/10.1007/978-3-319-28161-2
ISBN:	9783319281612$q(electronic bk.)

Self-organizing migrating algorithmmethodology and implementation /
Self-organizing migrating algorithmmethodology and implementation /[electronic resource] :edited by Donald Davendra, Ivan Zelinka. - Cham :Springer International Publishing :2016. - xviii, 289 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6261860-949X ;. - Studies in computational intelligence ;v. 216..

This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.

ISBN: 9783319281612$q(electronic bk.)

Standard No.: 10.1007/978-3-319-28161-2doiSubjects--Topical Terms:

231709
Evolutionary computation.

LC Class. No.: QA76.618

Dewey Class. No.: 006.3823

Self-organizing migrating algorithmmethodology and implementation /
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245 0 0 $a Self-organizing migrating algorithm $h [electronic resource] : $b methodology and implementation / $c edited by Donald Davendra, Ivan Zelinka.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xviii, 289 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.626
520 $a This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
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650 1 4 $a Engineering. $3 210888
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Optimization. $3 274084
700 1 $a Davendra, Donald. $3 338752
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