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dc.title | Complex network analysis in PSO as an fitness landscape classifier | en |
dc.contributor.author | Pluháček, Michal | |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Janoštík, Jakub | |
dc.contributor.author | Davendra, Donald David | |
dc.relation.ispartof | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 | |
dc.identifier.isbn | 9781509006229 | |
dc.date.issued | 2016 | |
dc.citation.spage | 3332 | |
dc.citation.epage | 3337 | |
dc.event.title | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 | |
dc.event.location | Vancouver | |
utb.event.state-en | Canada | |
utb.event.state-cs | Kanada | |
dc.event.sdate | 2016-07-24 | |
dc.event.edate | 2016-07-29 | |
dc.type | conferenceObject | |
dc.language.iso | en | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.identifier.doi | 10.1109/CEC.2016.7744211 | |
dc.relation.uri | http://ieeexplore.ieee.org/document/7744211/ | |
dc.subject | Complex network | en |
dc.subject | Fitness landscape analysis | en |
dc.subject | Particle swarm optimization | en |
dc.subject | PSO | en |
dc.description.abstract | In this paper, an initial small-scale study is carried out. It is proposed that using the complex network analysis it may be possible to make a classification of the fitness landscape type. A complex network is constructed from the inner dynamics of the population in PSO algorithm. The mean and maximal number of links in the network is then evaluated alongside with other basic statistic characteristics. It is shown on a basic function set that the number of links in the networks may vary significantly when facing unimodal and multimodal problems. Initial visualizations of the constructed complex networks are presented and the results are discussed with proposals for future research and possible future applications of this method. © 2016 IEEE. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1006961 | |
utb.identifier.obdid | 43876203 | |
utb.identifier.scopus | 2-s2.0-85008248837 | |
utb.identifier.wok | 000390749103067 | |
utb.source | d-wok | |
dc.date.accessioned | 2017-07-13T14:50:27Z | |
dc.date.available | 2017-07-13T14:50:27Z | |
utb.contributor.internalauthor | Pluháček, Michal | |
utb.contributor.internalauthor | Šenkeřík, Roman | |
utb.contributor.internalauthor | Viktorin, Adam | |
utb.contributor.internalauthor | Janoštík, Jakub | |
utb.fulltext.affiliation | Michal Pluhacek, Roman Senkerik, Adam Viktorin Jakub Janostik Faculty of Applied Informatics Tomas Bata University in Zlin T.G. Masaryka 5555, 760 01 Zlin, Czech Republic {pluhacek, senkerik, janostik,viktorin}@fai.utb.cz Donald Davendra Computer Science Department Central Washington University 400 E. University Way, Ellensburg, WA 98926-7520 USA. [email protected] | |
utb.fulltext.dates | - | |
utb.fulltext.sponsorship | This work was supported by Grant Agency of the Czech Republic – GACR P103/15/06700S, further by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014. Also by the 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/CebiaTech/2016/007. |