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Analytic programming powered by chaotic dynamics

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dc.title Analytic programming powered by chaotic dynamics en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Skanderová, Lenka
dc.contributor.author Šaloun, Petr
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Dao, Tran Trong
dc.contributor.author Hoang, Duy Vo
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 123
dc.citation.epage 129
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_12
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-07401-6_12
dc.description.abstract In this paper we discuss alternative tool for symbolic regression so called Analytical programming and compare its variants powered by classical random as well as chaotic random-like number generator. Experimental data are used from the previous experiments reported for genetic programming. Selected algorithms are differential evolution, SOMA, particle swarm, simulated annealing and evolutionary strategies. All of them are mutually used in scheme Master- Slave meta-evolution for final complex structure fitting and its parameter estimation. © Springer International Publishing Switzerland 2014 en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1004570
utb.identifier.obdid 43871972
utb.identifier.scopus 2-s2.0-84927643582
utb.source d-scopus
dc.date.accessioned 2015-05-28T11:39:23Z
dc.date.available 2015-05-28T11:39:23Z
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Ivan Zelinka1,3, Lenka Skanderova1, Petr Šaloun 1, Roman Senkerik2, Tran Trong Dao3, and Duy Vo Hoang3 1 VSB-Technical University of Ostrava, 17. listopadu 15 708 33, Ostrava-Poruba, Czech Republic ivan.zelinka@vsb.cz 2 Faculty of Applied Informatics, Tomas Bata University in Zlin, Czech Republic senkerik@fai.utb.cz 3 MERLIN, Ton Duc Thang University, 19 Nguyen Huu Tho Str., Dist. 7, Ho Chi Minh City, Vietnam ivan.zelinka@vsb.cz, {trantrongdao,vohoangduy}@tdt.edu.vn
utb.fulltext.dates -
utb.fulltext.sponsorship The following two grants are acknowledged for the financial support provided for this research: Grant Agency of the Czech Republic - GACR P103/13/08195S, 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, partially supported by Grant of SGS No. SP2013/159, VSB - Technical University of Ostrava, Czech Republic, and by European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089. Special thanks also belong to the research group MERLIN of Ton Duc Thang University, Ho Chi Minh City, Vietnam.
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