Chaos driven PSO with ensemble of priority factors

Pluháček, Michal; Šenkeřík, Roman; Zelinka, Ivan; Davendra, Donald David

dc.title	Chaos driven PSO with ensemble of priority factors	en
dc.contributor.author	Pluháček, Michal
dc.contributor.author	Šenkeřík, Roman
dc.contributor.author	Zelinka, Ivan
dc.contributor.author	Davendra, Donald David
dc.relation.ispartof	Advances in Intelligent Systems and Computing
dc.identifier.issn	2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn	978-3-319-07400-9
dc.date.issued	2014
utb.relation.volume	289
dc.citation.spage	89
dc.citation.epage	97
dc.event.title	International conference on prediction, modeling and analysis of complex systems, NOSTRADAMUS 2014
dc.event.location	Ostrava
utb.event.state-en	Czech Republic
utb.event.state-cs	Česká republika
dc.event.sdate	2012-06-23
dc.event.edate	2012-06-25
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	Springer-Verlag
dc.identifier.doi	10.1007/978-3-319-07401-6_9
dc.relation.uri	https://link.springer.com/chapter/10.1007/978-3-319-07401-6_9
dc.subject	Chaos	en
dc.subject	Ensemble learning	en
dc.subject	Evolutionary algorithm	en
dc.subject	Optimization	en
dc.subject	Particle swarm optimization	en
dc.subject	PSO	en
dc.description.abstract	In this paper a new approach for PSO algorithm driven by chaotic pseudorandom number generator is investigated. The ensemble learning method that has been successfully implemented in many evolutionary computational techniques is applied here for the selection of priority factors in the velocity calculations formula. The goal is to improve the performance of chaos driven PSO. The promising results are compared with previously published results of SPSO-2011 on the CEC´ 13 benchmark set. © Springer International Publishing Switzerland 2014	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1004574
utb.identifier.obdid	43871683
utb.identifier.scopus	2-s2.0-84927667878
utb.source	d-scopus
dc.date.accessioned	2015-05-28T11:39:24Z
dc.date.available	2015-05-28T11:39:24Z
utb.contributor.internalauthor	Pluháček, Michal
utb.contributor.internalauthor	Šenkeřík, Roman
utb.fulltext.affiliation	Michal Pluhacek 1 , Roman Senkerik 1 , Ivan Zelinka 2 , and Donald Davendra 2 1 Faculty of Applied Informatics Tomas Bata University in Zlin T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek,senkerik}@fai.utb.cz 2 Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic {ivan.zelinka,donald.davendra}@vsb.cz
utb.fulltext.dates	-
utb.fulltext.sponsorship	This work was supported by Grant Agency of the Czech Republic - GACR P103/13/08195S, Grants of SGS No. SP2014/159 and SP2014/170, VŠB - Technical University of Ostrava, Czech Republic, by the Development of human resources in research and development of latest soft computing methods and their application in practice project, reg. no. CZ.1.07/2.3.00/20.0072 funded by Operational Programme Education for Competitiveness, co-financed by ESF and state budget of the Czech Republic, by European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the project No. IGA/FAI/2014/010.