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dc.contributor.authorUysal, Mitat
dc.date.accessioned2015-04-29T06:18:03Z
dc.date.available2015-04-29T06:18:03Z
dc.date.issued2007
dc.identifier.citationUYSAL, M (2007). Comparison of ARIMA and RBFN models to predict the bank transactions. Information Technology Journal, 6 (3), pp. 475-477.en_US
dc.identifier.issn1812-5638
dc.identifier.urihttp://hdl.handle.net/11376/1460
dc.description.abstractF or making a prediction using time series, a large variety of approaches are available. Prediction of scalar time-series {x(n)} refers to the task of finding an estimate x(n+ 1) of the next future sample x(n+l) based on the knowledge of the history of time-series, i,e., the samples x(n), x(n-l), ... (Rank,2003).en_US
dc.language.isoengen_US
dc.publisherANSINETen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComparison of ARIMAen_US
dc.subjectRBFNen_US
dc.subjectBank Transactionen_US
dc.titleComparison of ARIMA and RBFN models to predict the bank transactionsen_US
dc.typearticleen_US
dc.relation.journalInformation Technology Journalen_US
dc.contributor.departmentDoğuş Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.contributor.authorIDTR115245en_US
dc.identifier.volume6en_US
dc.identifier.issue3en_US
dc.identifier.startpage475en_US
dc.identifier.endpage477en_US


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