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dc.title | Analysing knowledge transfer in SHADE via complex network | en |
dc.contributor.author | Viktorin, Adam | |
dc.contributor.author | Šenkeřík, Roman | |
dc.contributor.author | Pluháček, Michal | |
dc.contributor.author | Kadavý, Tomáš | |
dc.relation.ispartof | Logic Journal of the IGPL | |
dc.identifier.issn | 1367-0751 Scopus Sources, Sherpa/RoMEO, JCR | |
dc.date.issued | 2020 | |
utb.relation.volume | 28 | |
utb.relation.issue | 2 | |
dc.citation.spage | 153 | |
dc.citation.epage | 170 | |
dc.type | article | |
dc.language.iso | en | |
dc.publisher | Oxford Univ Press | |
dc.identifier.doi | 10.1093/jigpal/jzy042 | |
dc.relation.uri | https://academic.oup.com/jigpal/article-abstract/28/2/153/5107008?redirectedFrom=fulltext | |
dc.subject | differential evolution | en |
dc.subject | SHADE | en |
dc.subject | complex network | en |
dc.subject | centrality | en |
dc.subject | knowledge transfer | en |
dc.description.abstract | In this research paper a hybridization of two computational intelligence fields, which are evolutionary computation techniques and complex networks (CNs), is presented. During the optimization run of the success-history based adaptive differential evolution (SHADE) a CN is built and its feature, node degree centrality, is extracted for each node. Nodes represent here the individual solutions from the SHADE population. Edges in the network mirror the knowledge transfer between individuals in SHADE's population, and therefore, the node degree centrality can be used to measure knowledge transfer capabilities of each individual. The correlation between individual's quality and its knowledge transfer capability is recorded and analyzed on the CEC2015 benchmark set in three different dimensionality settings-10D, 30D and 50D. Results of the analysis are discussed, and possible directions for future research are suggested. | en |
utb.faculty | Faculty of Applied Informatics | |
dc.identifier.uri | http://hdl.handle.net/10563/1009871 | |
utb.identifier.obdid | 43880472 | |
utb.identifier.wok | 000559006600002 | |
utb.source | J-wok | |
dc.date.accessioned | 2020-09-01T10:09:21Z | |
dc.date.available | 2020-09-01T10:09:21Z | |
dc.description.sponsorship | Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST (European Cooperation in Science & Technology), Improving Applicability of NatureInspired Optimisation by Joining Theory and Practice (ImAppNIO) [CA15140]; COST (European Cooperation in Science & Technology), HighPerformance Modelling and Simulation for Big Data Applications (cHiPSet) [IC1406]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089] | |
utb.ou | CEBIA-Tech | |
utb.contributor.internalauthor | Viktorin, Adam | |
utb.contributor.internalauthor | Šenkeřík, Roman | |
utb.contributor.internalauthor | Pluháček, Michal | |
utb.contributor.internalauthor | Kadavý, Tomáš | |
utb.fulltext.affiliation | ADAM VIKTORIN *, ROMAN SENKERIK **, MICHAL PLUHACEK †, TOMAS KADAVY †† Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01 Zlin, Czech Republic ∗ E-mail: aviktorin@fai.utb.cz ∗∗ E-mail: senkerik@fai.utb.cz † E-mail: pluhacek@fai.utb.cz †† E-mail: kadavy@fai.utb.cz | |
utb.fulltext.dates | Received 25 September 2017 | |
utb.fulltext.sponsorship | This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by the Internal Grant Agency of Tomas Bata University under the Project no. IGA/CebiaTech/2018/003. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature- Inspired Optimisation by Joining Theory and Practice (ImAppNIO) and Action IC1406, High- Performance Modelling and Simulation for Big Data Applications (cHiPSet). The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz). | |
utb.wos.affiliation | [Viktorin, Adam; Senkerik, Roman; Pluhacek, Michal; Kadavy, Tomas] Tomas Bata Univ Zlin, Fac Appl Informat, TG Masaryka 5555, Zlin 76001, Czech Republic | |
utb.fulltext.projects | LO1303 | |
utb.fulltext.projects | MSMT-7778/2014 | |
utb.fulltext.projects | CZ.1.05/2.1.00/03.0089 | |
utb.fulltext.projects | IGA/CebiaTech/2018/003 | |
utb.fulltext.projects | CA15140 | |
utb.fulltext.projects | ImAppNIO | |
utb.fulltext.projects | IC1406 | |
utb.fulltext.projects | cHiPSet | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.faculty | Faculty of Applied Informatics | |
utb.fulltext.faculty | Faculty of Applied Informatics |