Chaos particle swarm optimization with Eensemble of chaotic systems

dc.contributor.author	Pluháček, Michal
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Davendra, Donald David
dc.date.accessioned	2016-02-22T13:50:09Z
dc.date.available	2016-02-22T13:50:09Z
dc.date.issued	2015
dc.description.abstract	In this study the Chaotic Particle Swarm Optimization (CPSO) algorithm with six simultaneously used chaotic pseudo-random number generators (CPRNG) is investigated. The implementation of chaotic sequences is detailed and discussed. The Ensemble learning approach is used for assigning CPRNGs to particles. The results of proposed algorithm on IEEE CEC′13 Real-Parameter Single Objective Optimization benchmark set are presented and compared with the SPSO-2011.	cs
dc.description.firstpage	29	cs
dc.description.lastpage	35	cs
dc.description.source	Web of Science	cs
dc.description.volume	25	cs
dc.identifier.citation	Swarm and Evolutionary Computation. 2015, vol. 25, p. 29-35.	cs
dc.identifier.doi	10.1016/j.swevo.2015.10.008
dc.identifier.issn	2210-6502
dc.identifier.issn	2210-6510
dc.identifier.uri	http://hdl.handle.net/10084/111301
dc.identifier.wos	000367860600004
dc.language.iso	en	cs
dc.publisher	Elsevier	cs
dc.relation.ispartofseries	Swarm and Evolutionary Computation	cs
dc.relation.uri	http://dx.doi.org/10.1016/j.swevo.2015.10.008	cs
dc.rights	Copyright © 2015 Elsevier B.V. All rights reserved.	cs
dc.title	Chaos particle swarm optimization with Eensemble of chaotic systems	cs
dc.type	article	cs
dc.type.status	Peer-reviewed	cs

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