Finding an optimal interval length in high order fuzzy time series

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dc.authorid0000-0003-4301-4149
dc.contributor.authorEgrioglu, Erol
dc.contributor.authorAladag, Cagdas Hakan
dc.contributor.authorYolcu, Ufuk
dc.contributor.authorUslu, Vedide R.
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.abstractUnivariate fuzzy time series approaches which have been widely used in recent years can be divided into two classes, which are called first order and high order models. In the literature, it has been shown that high order fuzzy time series approaches improve the forecasting accuracy. One of the important parts of obtaining high accuracy forecasts in fuzzy time series is that the length of interval is very vital. As mentioned in the first-order models by Egrioglu, Aladag, Basaran, Uslu, and Yolcu (2009), the length of interval also plays very important role in high order models too. In this study, a new approach which uses an optimization technique with a single-variable constraint is proposed to determine an optimal interval length in high order fuzzy time series models. An optimization procedure is used in order to determine optimum length of interval for the best forecasting accuracy, we used optimization procedure. In the optimization process, we used a MATLAB function employing an algorithm based on golden section search and parabolic interpolation. The proposed method was employed to forecast the enrollments of the University of Alabama to show the considerable outperforming results. (C) 2009 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.eswa.2009.12.006
dc.identifier.endpage5055
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue7
dc.identifier.scopus2-s2.0-77950189383
dc.identifier.scopusqualityQ1
dc.identifier.startpage5052
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2009.12.006
dc.identifier.urihttps://hdl.handle.net/11480/4867
dc.identifier.volume37
dc.identifier.wosWOS:000277726300038
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONS
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectForecasting
dc.subjectFuzzy sets
dc.subjectHigh order fuzzy time series forecasting model
dc.subjectLength of interval
dc.subjectOptimization
dc.titleFinding an optimal interval length in high order fuzzy time series
dc.typeArticle

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