hGA: Hybrid Genetic Algorithm in Fuzzy Rule-based Classification Systems for High-dimensional Problems

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dc.contributor.authorKizilkaya Aydogan, Emel
dc.contributor.authorKaraoglan, Ismail
dc.contributor.authorPardalos, Panos M.
dc.date.accessioned2020-03-26T18:30:40Z
dc.date.available2020-03-26T18:30:40Z
dc.date.issued2012
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe aim of this work is to propose a hybrid heuristic approach (called hGA) based on genetic algorithm (GA) and integer-programming formulation (IPF) to solve high dimensional classification problems in linguistic fuzzy rule-based classification systems. In this algorithm, each chromosome represents a rule for specified class, GA is used for producing several rules for each class, and finally IPF is used for selection of rules from a pool of rules, which are obtained by GA. The proposed algorithm is experimentally evaluated by the use of non-parametric statistical tests on seventeen classification benchmark data sets. Results of the comparative study show that hGA is able to discover accurate and concise classification rules. Published by Elsevier B.V.en_US
dc.description.sponsorshipLATNA Laboratory, National Research University Higher School of Economics, RF government [ag. 11.G34.31.0057]en_US
dc.description.sponsorshipPartially supported by LATNA Laboratory, National Research University Higher School of Economics, RF government grant, ag. 11.G34.31.0057.en_US
dc.identifier.citationKızılkaya Aydogan, E., Karaoglan, I., Pardalos, P. M., (2012). hGA: Hybrid Genetic Algorithm in Fuzzy Rule-based Classification Systems for High-dimensional Problems. Applied Soft Computing. 12(2), 800-806. doi:10.1016/j.asoc.2011.10.010
dc.identifier.doi10.1016/j.asoc.2011.10.010en_US
dc.identifier.endpage806en_US
dc.identifier.issn1568-4946en_US
dc.identifier.issn1872-9681en_US
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage800en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.asoc.2011.10.010
dc.identifier.urihttps://hdl.handle.net/20.500.12395/28107
dc.identifier.volume12en_US
dc.identifier.wosWOS:000298631400021en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorKaraoglan, Ismail
dc.language.isoenen_US
dc.publisherElsevier Science Bven_US
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectFuzzy rule based classification systemsen_US
dc.subjectGenetic algorithmsen_US
dc.subjectGenetic fuzzy systemsen_US
dc.subjectClassificationen_US
dc.subjectInteger programmingen_US
dc.titlehGA: Hybrid Genetic Algorithm in Fuzzy Rule-based Classification Systems for High-dimensional Problemsen_US
dc.typeArticleen_US

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