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Study on the development of complex network for evolutionary and swarm based algorithms

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dc.title Study on the development of complex network for evolutionary and swarm based algorithms en
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Zelinka, Ivan
dc.contributor.author Pluháček, Michal
dc.contributor.author Viktorin, Adam
dc.relation.ispartof Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.identifier.issn 0302-9743 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9783319624273
dc.date.issued 2017
utb.relation.volume 10062 LNAI
dc.citation.spage 151
dc.citation.epage 161
dc.event.title 15th Mexican International Conference on Artificial Intelligence, MICAI 2016
dc.event.location Cancún
utb.event.state-en Mexico
utb.event.state-cs Mexiko
dc.event.sdate 2016-10-23
dc.event.edate 2016-10-28
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-319-62428-0_12
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-62428-0_12
dc.subject Complex networks en
dc.subject Graphs en
dc.subject Analysis en
dc.subject Differential Evolution en
dc.subject PSO en
dc.description.abstract This contribution deals with the hybridization of complex network frameworks and metaheuristic algorithms. The population is visualized as an evolving complex network that exhibits non-trivial features. It briefly investigates the time and structure development of a complex network within a run of selected metaheuristic algorithms – i.e. PSO and Differential Evolution (DE). Two different approaches for the construction of complex networks are presented herein. It also briefly discusses the possible utilization of complex network attributes. These attributes include an adjacency graph that depicts interconnectivity, while centralities provide an overview of convergence and stagnation, and clustering encapsulates the diversity of the population, whereas other attributes show the efficiency of the network. The experiments were performed for one selected DE/PSO strategy and one simple test function. © Springer International Publishing AG 2017. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007478
utb.identifier.obdid 43877303
utb.identifier.scopus 2-s2.0-85028473117
utb.identifier.wok 000434213700012
utb.source d-scopus
dc.date.accessioned 2017-09-14T09:00:53Z
dc.date.available 2017-09-14T09:00:53Z
dc.description.sponsorship ERDF, European Regional Development Fund; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; P103/15/06700S, GACR;GAČR, Grantová Agentura České Republiky
dc.description.sponsorship Grant Agency of the Czech Republic GACR [P103/15/06700S]; Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the project CEBIA [CZ.1.05/2.1.00/03.0089]; SGS of VSB Technical University of Ostrava, Czech Republic [SP2016/175]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2016/007]
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Zelinka, Ivan
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Viktorin, Adam
utb.wos.affiliation [Senkerik, Roman; Pluhacek, Michal; Viktorin, Adam] Tomas Bata Univ Zlin, Fac Appl Informat, Nam TG Masaryka 5555, Zlin 76001, Czech Republic; [Zelinka, Ivan] Tech Univ Ostrava, Fac Elect Engn & Comp Sci, 17 Listopadu 15, Ostrava 70833, Czech Republic
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam T.G. Masaryka 5555, Zlin, Czech Republic; Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, 17. uistopadu 15, Ostrava-Poruba, Czech Republic
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