Analytic programming powered by chaotic dynamics

Zelinka, Ivan; Skanderová, Lenka; Šaloun, Petr; Šenkeřík, Roman; Dao, Tran Trong; Hoang, Duy Vo

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	978-3-319-07400-9
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 [email protected] 2 Faculty of Applied Informatics, Tomas Bata University in Zlin, Czech Republic [email protected] 3 MERLIN, Ton Duc Thang University, 19 Nguyen Huu Tho Str., Dist. 7, Ho Chi Minh City, Vietnam [email protected], {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.