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Fuzzy clustering to classify several time series models with fractional Brownian motion errors

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dc.contributor.author Mahmoudi, Mohammad Reza
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Qasem, Sultan Noman
dc.contributor.author Mosavi, Amirhosein
dc.contributor.author S. Band, Shahab
dc.date.accessioned 2022-05-11T10:52:44Z
dc.date.available 2022-05-11T10:52:44Z
dc.date.issued 2021-02
dc.identifier.citation Mahmoudi, Mohammad Reza...et al. (2021). "Fuzzy clustering to classify several time series models with fractional Brownian motion errors", Alexandria Engineering Journal, Vol. 60, No. 1, pp. 1137-1145. tr_TR
dc.identifier.issn 1110-0168
dc.identifier.uri http://hdl.handle.net/20.500.12416/5493
dc.description.abstract In real world problems, scientists aim to classify and cluster several time series processes that can be used for a dataset. In this research, for the first time, based on fuzzy clustering method, an approach is applied to classify and cluster several time series models with fractional Brownian motion errors as candidates to fit on a dataset. The ability of the introduced technique is studied using simulation and real world example. © 2020 THE AUTHORS tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1016/j.aej.2020.10.037 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Classification tr_TR
dc.subject Fractional Brownian Motion tr_TR
dc.subject Fuzzy Clustering tr_TR
dc.subject Non-Stationary tr_TR
dc.subject RDI tr_TR
dc.subject Stationary tr_TR
dc.subject Time Series tr_TR
dc.title Fuzzy clustering to classify several time series models with fractional Brownian motion errors tr_TR
dc.type article tr_TR
dc.relation.journal Alexandria Engineering Journal tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 60 tr_TR
dc.identifier.issue 1 tr_TR
dc.identifier.startpage 1137 tr_TR
dc.identifier.endpage 1145 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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