國立虎尾科技大學 |

Advances of Evolutionary Computation: Methods and Operators

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances of Evolutionary Computation: Methods and Operators/ by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro.
作者:	Cuevas, Erik.
其他作者:	Díaz Cortés, Margarita Arimatea.
面頁冊數:	XIV, 202 p. 48 illus., 5 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-319-28503-0
ISBN:	9783319285030

Advances of Evolutionary Computation: Methods and Operators
Cuevas, Erik.

Advances of Evolutionary Computation: Methods and Operators[electronic resource] /by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro. - 1st ed. 2016. - XIV, 202 p. 48 illus., 5 illus. in color.online resource. - Studies in Computational Intelligence,6291860-949X ;. - Studies in Computational Intelligence,564.

Introduction -- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider.-A States of Matter Algorithm for Global Optimization -- An Algorithm for Global Optimization Inspired by Collective Animal Behavior -- A Bio-inspired Evolutionary Algorithm: Allostatic Optimization -- Optimization Based on the Behavior of Locust Swarms. .

The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be eﬀective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.

ISBN: 9783319285030

Standard No.: 10.1007/978-3-319-28503-0doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advances of Evolutionary Computation: Methods and Operators
LDR:02543nam a22004095i 4500 001 980583
003 DE-He213
005 20200701030713.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319285030 $9 978-3-319-28503-0
024 7 $a 10.1007/978-3-319-28503-0 $2 doi
035 $a 978-3-319-28503-0
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Cuevas, Erik. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1102812
245 1 0 $a Advances of Evolutionary Computation: Methods and Operators $h [electronic resource] / $c by Erik Cuevas, Margarita Arimatea Díaz Cortés, Diego Alberto Oliva Navarro.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XIV, 202 p. 48 illus., 5 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Computational Intelligence, $x 1860-949X ; $v 629
505 0 $a Introduction -- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider.-A States of Matter Algorithm for Global Optimization -- An Algorithm for Global Optimization Inspired by Collective Animal Behavior -- A Bio-inspired Evolutionary Algorithm: Allostatic Optimization -- Optimization Based on the Behavior of Locust Swarms. .
520 $a The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be eﬀective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Díaz Cortés, Margarita Arimatea. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1273304
700 1 $a Oliva Navarro, Diego Alberto. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1104805
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319285023
776 0 8 $i Printed edition: $z 9783319285047
776 0 8 $i Printed edition: $z 9783319803661
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-3-319-28503-0
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)