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Advances of evolutionary computation[electronic resource] :methods and operators /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3823
書名/作者:	Advances of evolutionary computation : methods and operators // by Erik Cuevas, Margarita Arimatea Diaz Cortes, Diego Alberto Oliva Navarro.
作者:	Cuevas, Erik.
其他作者:	Diaz Cortes, Margarita Arimatea.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xiv, 202 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Evolutionary computation.
標題:	Engineering.
標題:	Computational Intelligence.
標題:	Artificial Intelligence (incl. Robotics)
ISBN:	9783319285030
ISBN:	9783319285023
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-28503-0

Advances of evolutionary computation[electronic resource] :methods and operators /
Cuevas, Erik.

Advances of evolutionary computationmethods and operators /[electronic resource] :by Erik Cuevas, Margarita Arimatea Diaz Cortes, Diego Alberto Oliva Navarro. - Cham :Springer International Publishing :2016. - xiv, 202 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6291860-949X ;. - Studies in computational intelligence ;v.379..

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:

404545
Evolutionary computation.

LC Class. No.: QA76.618

Dewey Class. No.: 006.3823

Advances of evolutionary computation[electronic resource] :methods and operators /
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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.
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