ANN-polynomial-Fourier series modeling and Monte Carlo forecasting of tourism data

dc.authoridDanbatta, Salim Jibrin/0000-0002-8913-5766en_US
dc.authoridVarol, Asaf/0000-0003-1606-4079en_US
dc.contributor.authorDanbatta, Salim Jibrin
dc.contributor.authorVarol, Asaf
dc.date.accessioned2024-07-12T21:37:29Z
dc.date.available2024-07-12T21:37:29Z
dc.date.issued2022en_US
dc.department[Belirlenecek]en_US
dc.description.abstractModeling and forecasting of tourism data have received attention in the past decades. Turkey is one of the countries that benefit significantly from the tourism industry. Several time-series models have been recommended to best describe tourist arrivals to Turkey. However, in the 21st century, the world experiences great uncertainty in most possible event outcomes. These uncertainties are very difficult to account for. We proposed a hybrid artificial neural network (ANN)-polynomial-Fourier method to model the number of foreign visitors to Turkey from January 2004 to December 2020. The proposed model performance before and during the COVID-19 pandemic is evaluated separately. We evaluate the model performance by comparing with results from Danbatta and Varol (2021, ), Fourier series, and ARIMA models. To account for prediction uncertainties, we ran 300 Monte Carlo simulations within +/- 2 sigma from the model regression curve. According to the result outcomes, the proposed ANN-polynomial-Fourier has proven worthy to be considered a candidate model for the Turkish tourism data. The multistep ahead forecast suggests a 10.22% increase in the monthly foreign visitors' arrivals to Turkey in the year 2021.en_US
dc.identifier.doi10.1002/for.2845
dc.identifier.endpage932en_US
dc.identifier.issn0277-6693
dc.identifier.issn1099-131X
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85122281644en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage920en_US
dc.identifier.urihttps://doi.org/10.1002/for.2845
dc.identifier.urihttps://hdl.handle.net/20.500.12415/6809
dc.identifier.volume41en_US
dc.identifier.wosWOS:000739701100001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofJournal of Forecastingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY04151
dc.subjectFourier Seriesen_US
dc.subjectModelingen_US
dc.subjectMonte Carlo Simulationen_US
dc.subjectTime-Series Forecastingen_US
dc.subjectTurkish Tourismen_US
dc.titleANN-polynomial-Fourier series modeling and Monte Carlo forecasting of tourism dataen_US
dc.typeArticle
dspace.entity.typePublication

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