Monte Carlo forecasting of time series data using Polynomial-Fourier series model

dc.authoridVarol, Asaf/0000-0003-1606-4079en_US
dc.authoridDanbatta, Salim Jibrin/0000-0002-8913-5766en_US
dc.contributor.authorDanbatta, Salim Jibrin
dc.contributor.authorVarol, Asaf
dc.date.accessioned2024-07-12T21:37:58Z
dc.date.available2024-07-12T21:37:58Z
dc.date.issued2021en_US
dc.department[Belirlenecek]en_US
dc.description.abstractThe perishable nature of tourism products and services makes forecasting an important tool for tourism planning, especially in the current COVID-19 pandemic time. The forecast assists tourism organizations in decision-making regarding resource allocations to avoid shortcomings. This study is motivated by the need to model periodic time series with linear and nonlinear trends. A hybrid Polynomial-Fourier series model that uses the combination of polynomial and Fourier fittings to capture and forecast time series data was proposed. The proposed model is applied to monthly foreign visitors to Turkey from January 2014 to August 2020 dataset and diagnostic checks show that the proposed model produces a statistically good fit. To improve the model forecast, a Monte Carlo simulation scheme with 100 simulation paths is applied to the model residue. The mean of the 100 simulation paths within +/- 2 sigma bounds from the model curve was taken and found to give statistically acceptable results.en_US
dc.identifier.doi10.1142/S179396232141004X
dc.identifier.issn1793-9623
dc.identifier.issn1793-9615
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85099762430en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.urihttps://doi.org/10.1142/S179396232141004X
dc.identifier.urihttps://hdl.handle.net/20.500.12415/7000
dc.identifier.volume12en_US
dc.identifier.wosWOS:000663028900003en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartofInternational Journal of Modeling Simulation And Scientific Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY04342
dc.subjectTime Series Forecastingen_US
dc.subjectMonte Carloen_US
dc.subjectFourier Seriesen_US
dc.subjectPolynomialen_US
dc.subjectCovid-19en_US
dc.titleMonte Carlo forecasting of time series data using Polynomial-Fourier series modelen_US
dc.typeArticle
dspace.entity.typePublication

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