Improving weighted information criterion by using optimization

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dc.authorid0000-0003-4301-4149
dc.contributor.authorAladag, Cagdas Hakan
dc.contributor.authorEgrioglu, Erol
dc.contributor.authorGunay, Suleyman
dc.contributor.authorBasaran, Murat A.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2010
dc.departmentNiğde ÖHÜ
dc.description.abstractAlthough artificial neural networks (ANN) have been widely used in forecasting time series, the determination of the best model is still a problem that has been studied a lot. Various approaches available in the literature have been proposed in order to select the best model for forecasting in ANN in recent years. One of these approaches is to use a model selection strategy based on the weighted information criterion (WIC). WIC is calculated by summing weighted different selection criteria which measure the forecasting accuracy of an ANN model in different ways. In the calculation of WIC, the weights of different selection criteria are determined heuristically. In this study, these weights are calculated by using optimization in order to obtain a more consistent criterion. Four real time series are analyzed in order to show the efficiency of the improved WIC. When the weights are determined based on the optimization, it is obviously seen that the improved WIC produces better results. (C) 2009 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.cam.2009.11.016
dc.identifier.endpage2687
dc.identifier.issn0377-0427
dc.identifier.issue10
dc.identifier.scopus2-s2.0-73449108019
dc.identifier.scopusqualityQ2
dc.identifier.startpage2683
dc.identifier.urihttps://dx.doi.org/10.1016/j.cam.2009.11.016
dc.identifier.urihttps://hdl.handle.net/11480/4895
dc.identifier.volume233
dc.identifier.wosWOS:000274554900021
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherELSEVIER SCIENCE BV
dc.relation.ispartofJOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectArtificial neural networks
dc.subjectConsistency
dc.subjectForecasting
dc.subjectModel selection
dc.subjectTime series
dc.subjectWeighted information criterion
dc.titleImproving weighted information criterion by using optimization
dc.typeArticle

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