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Chaos driven PSO with ensemble of priority factors

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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 9783319074009
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.
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