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An investigation on evolutionary identification of continuous chaotic systems

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dc.title An investigation on evolutionary identification of continuous chaotic systems en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Davendra, Donald David
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Jašek, Roman
dc.relation.ispartof Proceedings of the Fourth Global Conference on Power Control and Optimization
dc.identifier.issn 0094-243X Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-0-7354-0893-7
dc.date.issued 2011
utb.relation.volume 1337
dc.citation.spage 280
dc.citation.epage 284
dc.event.title 4th Global Conference on Power Control and Optimization
dc.event.location Sarawak
utb.event.state-en Malaysia
utb.event.state-cs Malajsie
dc.event.sdate 2010-12-02
dc.event.edate 2010-12-04
dc.type conferenceObject
dc.language.iso en
dc.publisher American Institute of Physics (AIP) en
dc.identifier.doi 10.1063/1.3592478
dc.relation.uri http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=APCPCS001337000001000280000001&idtype=cvips&gifs=yes&ref=no
dc.subject SOMA en
dc.subject Lorenz system en
dc.subject PSO en
dc.description.abstract This paper discusses the possibility of using evolutionary algorithms for the reconstruction of chaotic systems. The main aim of this work is to show that evolutionary algorithms are capable of the reconstruction of chaotic systems without any partial knowledge of internal structure, i.e. based only on measured data. Algorithm SOMA was used in reported experiments here. Systems selected for numerical experiments here is the well-known Lorenz system. For each algorithm and its version, repeated simulations were done, totaling 20 simulations. According to obtained results it can be stated that evolutionary reconstruction is an alternative and promising way as to how to identify chaotic systems. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1001729
utb.identifier.rivid RIV/70883521:28140/10:63508873!RIV11-MSM-28140___
utb.identifier.obdid 43864731
utb.identifier.scopus 2-s2.0-80051561796
utb.identifier.wok 000291830300043
utb.source d-wok
dc.date.accessioned 2011-08-09T07:33:39Z
dc.date.available 2011-08-09T07:33:39Z
dc.rights.access openAccess
utb.contributor.internalauthor Zelinka, Ivan
utb.contributor.internalauthor Davendra, Donald David
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Jašek, Roman
utb.fulltext.affiliation Ivan Zelinka1,2, Donald Davendra1 , Roman Senkerik1 and Roman Jasek1 1 Department of Informatics and Artificial Intelligence, Tomas Bata University in Zlin, Nad Stráněmi 4511, Zlin 76001, Czech Republic. 2 Department of Computer Science, Faculty of Electrical Engineering and Computer Science VSB-TUO, 17. listopadu 15, 708 33 Ostrava-Poruba, {zelinka,davendra,senkerik,jasek}@fai.utb.cz, ivan.zelinka@vsb.cz, Czech Republic
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by grant No. MSM 7088352101 of the Ministry of Education of the Czech Republic and by grants of the Grant Agency of the Czech Republic GACR 102/09/1680
utb.fulltext.projects MSM 7088352101
utb.fulltext.projects GAČR 102/09/1680
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou Department of Informatics and Artificial Intelligence
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