A New Approach Based on Artificial Neural Networks for High Order Bivariate Fuzzy Time Series

Basit Öğe Kaydı
dc.authorid0000-0003-4301-4149
dc.contributor.authorEgrioglu, Erol
dc.contributor.authorUslu, V. Rezan
dc.contributor.authorYolcu, Ufuk
dc.contributor.authorBasaran, M. A.
dc.contributor.authorHakan, Aladag C.
dc.contributor.editorMehnen, J
dc.contributor.editorKoppen, M
dc.contributor.editorSaad, A
dc.contributor.editorTiwari, A
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2009
dc.departmentNiğde ÖHÜ
dc.description13th World Conference on Soft Computing in Industrial Application -- 2008 -- ELECTR NETWORK
dc.description.abstractWhen observations of time series are defined linguistically or do not follow the assumptions required for time series theory, the classical methods of time series analysis do not cope with fuzzy numbers and assumption violations. Therefore, forecasts are not reliable. [8], [9] gave a definition of fuzzy time series which have fuzzy observations and proposed a forecast method for it. In recent years, many researches about univariate fuzzy time series have been conducted. In [6], [5], [7], [4] and [10] bivariate fuzzy time series approaches have been proposed. In this study, a new method for high order bivariate fuzzy time series in which fuzzy relationships are determined by artificial neural networks (ANN) is proposed and the real data application of the proposed method is presented.
dc.description.sponsorshipWorld Federat Soft Comp, IEEE Ind Applicat Soc, IEEE UKRI Sect, Elsevier
dc.identifier.doi10.1007/978-3-540-89619-7_26
dc.identifier.endpage+
dc.identifier.isbn978-3-540-89618-0
dc.identifier.issn1867-5662
dc.identifier.scopus2-s2.0-79551652450
dc.identifier.scopusqualityN/A
dc.identifier.startpage265
dc.identifier.urihttps://dx.doi.org/10.1007/978-3-540-89619-7_26
dc.identifier.urihttps://hdl.handle.net/11480/5122
dc.identifier.volume58
dc.identifier.wosWOS:000269657800026
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherSPRINGER
dc.relation.ispartofAPPLICATIONS OF SOFT COMPUTING: FROM THEORY TO PRAXIS
dc.relation.ispartofseriesAdvances in Intelligent and Soft Computing
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleA New Approach Based on Artificial Neural Networks for High Order Bivariate Fuzzy Time Series
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu