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Maximizing vector distances for purpose of searching - A study of differential evolution suitability

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dc.title Maximizing vector distances for purpose of searching - A study of differential evolution suitability en
dc.contributor.author Kolařík, Martin
dc.contributor.author Jašek, Roman
dc.contributor.author Komínková Oplatková, Zuzana
dc.relation.ispartof Proceedings of the Fifth International Conference on Innovations in Bio-inspired Computing and Applications (IBICA 2014)
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-319-08155-7
dc.identifier.isbn 978-3-319-08156-4
dc.date.issued 2014
utb.relation.volume 303
dc.citation.spage 419
dc.citation.epage 428
dc.event.title 5th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA)
dc.event.location Ostrava
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2014-06-23
dc.event.edate 2014-06-25
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer-Verlag Berlin
dc.identifier.doi 10.1007/978-3-319-08156-4_42
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-08156-4_42
dc.subject optimization en
dc.subject differential evolution en
dc.subject distance metric en
dc.subject nonlinear en
dc.description.abstract This paper explores suitability of using of differential evolution for maximizing of weighted distances of vectors in a set of vectors. Increase in vector distances simplifies searching for the best matching vector what is a common task in many areas (for instance in biometric identification of people). Maximizing of weighted distances itself is complex and nonlinear problem. The differential evolution is efficient enough and helps in decreasing of the computational complexity space compared to enumerative methods where all possible combinations are calculated. To find out, if differential evolution can help with the problem, model experiments were introduced and executed. Experiments showed that differential evolution is able to resolve the problem. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003921
utb.identifier.obdid 43871870
utb.identifier.scopus 2-s2.0-84906684878
utb.identifier.wok 000342841800042
utb.source d-wok
dc.date.accessioned 2014-11-25T08:53:31Z
dc.date.available 2014-11-25T08:53:31Z
utb.contributor.internalauthor Kolařík, Martin
utb.contributor.internalauthor Jašek, Roman
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.fulltext.affiliation Martin Kolařík, Roman Jašek, and Zuzana Komínková Oplatková Tomas Bata University in Zlin, Faculty of Applied Informatics, Nám. T.G. Masaryka 5555, 760 01 Zlín, Czech Republic martin.kolarik@email.cz, {jasek,oplatkova}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.sponsorship This work was supported by the European Regional Development Fund under the project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089, by Internal Grant Agency at Tomas Bata University in Zlin, project nr. IGA/FAI/2014/054 and by the Bio-Inspired Methods: research, development and knowledge transfer project, reg. no. CZ.1.07/2.3.00/20.0073 funded by Operational Programme Education for Competitiveness, co- financed by ESF and state budget of the Czech Republic.
utb.fulltext.projects CZ.1.05/2.1.00/03.0089
utb.fulltext.projects CZ.1.07/2.3.00/20.0073
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