Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm

This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PS...

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Detalles Bibliográficos
Autores principales: Couceiro, Micael, Ghamisi, Pedram
Lenguaje:eng
Publicado: Springer 2015
Materias:
Mathematical Physics and Mathematics
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-19635-0
http://cds.cern.ch/record/2043037
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author Couceiro, Micael
Ghamisi, Pedram
author_facet Couceiro, Micael
Ghamisi, Pedram
author_sort Couceiro, Micael
collection CERN
description This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, suc
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
publisher Springer
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spelling cern-20430372021-04-21T20:07:01Zdoi:10.1007/978-3-319-19635-0http://cds.cern.ch/record/2043037engCouceiro, MicaelGhamisi, PedramFractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithmMathematical Physics and Mathematics This book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, sucSpringeroai:cds.cern.ch:20430372015
spellingShingle Mathematical Physics and Mathematics
Couceiro, Micael
Ghamisi, Pedram
Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title_full Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title_fullStr Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title_full_unstemmed Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title_short Fractional order Darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
title_sort fractional order darwinian particle swarm optimization: applications and evaluation of an evolutionary algorithm
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-19635-0
http://cds.cern.ch/record/2043037
work_keys_str_mv AT couceiromicael fractionalorderdarwinianparticleswarmoptimizationapplicationsandevaluationofanevolutionaryalgorithm
AT ghamisipedram fractionalorderdarwinianparticleswarmoptimizationapplicationsandevaluationofanevolutionaryalgorithm

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