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dc.rights.licenseVisos teisės saugomos / All rights reserveden_US
dc.contributor.authorDzidolikaitė, Agnė
dc.date.accessioned2025-11-20T14:08:32Z
dc.date.available2025-11-20T14:08:32Z
dc.date.issued2015
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/159423
dc.description.abstractIn many research fields we have to deal with multidimensional data. Multidimensional data should be provided in a form that researcher could understand the structure of the given data. Graphical data visualization could be used for this purpose. One of the methods of graphical data visualization is multidimensional scaling. Using multidimensional scaling higher dimension data is visualized in two or three dimensional space. In this paper genetic algorithm is combined with multidimensional scaling technique. Genetic algorithms usually mimic natural evolution and consist of selection, recombination and mutation. The new hybrid genetic algorithm is analyzed with beverages dataset and pharmacological dataset.en_US
dc.format.extent4 p.en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/159386en_US
dc.source.urihttps://ieeexplore.ieee.org/document/7119482en_US
dc.subjectmultidimensional scalingen_US
dc.subjectgenetic algorithmen_US
dc.subjectbeverages dataen_US
dc.subjectpharmacological dataen_US
dc.titleHybrid genetic algorithmen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.issued2015-06-08
dcterms.references13en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionVilnius Universityen_US
dcterms.sourcetitle2015 Open Conference of Electrical, Electronic and Information Sciences (eStream), April 21, 2015, Vilnius, Lithuaniaen_US
dc.identifier.eisbn9781467374453en_US
dc.publisher.nameIEEEen_US
dc.publisher.countryUnited States of Americaen_US
dc.publisher.cityNew Yorken_US
dc.identifier.doihttps://doi.org/10.1109/eStream.2015.7119482en_US


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