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dc.contributor.authorMammadov, Mammadağha
dc.contributor.authorYazıcı, Berna
dc.contributor.authorYolaçan, Ş.
dc.contributor.authorAslanargun, A.
dc.contributor.authorYüzer, Ali Fuat
dc.contributor.authorAğaoğlu, E.
dc.date.accessioned2019-10-20T09:31:38Z
dc.date.available2019-10-20T09:31:38Z
dc.date.issued2006
dc.identifier.issn1538-9472
dc.identifier.urihttps://hdl.handle.net/11421/17748
dc.description.abstractArtificial Neural Networks and statistical methods are applied on real data sets for forecasting, classification, and clustering problems. Hybrid models for two components are examined on different data sets; tourist arrival forecasting to Turkey, macro-economic problem on rescheduling of the countries' international debts, and grouping twenty-five European Union member and four candidate countries according to macro-economic indicators. Copyright © 2006 JMASM, Inc.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArimaen_US
dc.subjectCluster Analysisen_US
dc.subjectHybrid Modelsen_US
dc.subjectKohonen Netsen_US
dc.subjectLogistic And Probit Regressionen_US
dc.subjectMaastricht Criteriaen_US
dc.subjectNeural Networksen_US
dc.subjectRescheduling And Non-Rescheduling Of The International Debtsen_US
dc.subjectTime Seriesen_US
dc.titleStatistical methods and artificial neural networksen_US
dc.typearticleen_US
dc.relation.journalJournal of Modern Applied Statistical Methodsen_US
dc.contributor.departmentAnadolu Üniversitesi, Fen Fakültesi, İstatistik Bölümüen_US
dc.identifier.volume5en_US
dc.identifier.issue2en_US
dc.identifier.startpage495en_US
dc.identifier.endpage512en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorYazıcı, Berna
dc.contributor.institutionauthorYüzer, Ali Fuat


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