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dc.contributor.authorElikucuk, I.
dc.contributor.authorDuman, Ekrem
dc.date.accessioned2016-02-16T10:26:09Z
dc.date.available2016-02-16T10:26:09Z
dc.date.issued2013
dc.identifier.isbn978-3-642-40319-4
dc.identifier.urihttp://hdl.handle.net/10679/2623
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-642-40319-4_36
dc.description.abstractWe discuss how the Migrating Birds Optimization algorithm (MBO) is applied to statistical credit card fraud detection problem. MBO is a recently proposed metaheuristic algorithm which is inspired by the V flight formation of the migrating birds and it was shown to perform very well in solving a combinatorial optimization problem, namely the quadratic assignment problem. As analyzed in this study, it has a very good performance in the fraud detection problem also when compared to classical data mining and genetic algorithms. Its performance is further increased by the help of some modified neighborhood definitions and benefit mechanisms.
dc.language.isoengen_US
dc.publisherSpringer Science+Business Media
dc.relation.ispartofTrends and Applications in Knowledge Discovery and Data Mining
dc.rightsrestrictedAccess
dc.titleApplying migrating birds optimization to credit card fraud detectionen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID142351
dc.contributor.ozuauthorDuman, Ekrem
dc.identifier.volume7867
dc.identifier.startpage416
dc.identifier.endpage427
dc.identifier.doi10.1007/978-3-642-40319-4_36
dc.subject.keywordsMigrating birds optimization algorithm
dc.subject.keywordsFraud
dc.subject.keywordsCredit cards
dc.subject.keywordsGenetic algorithms
dc.identifier.scopusSCOPUS:2-s2.0-84892838750
dc.contributor.authorMale1


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