Deep learning models for airport demand forecasting with google trends: A case study of Madrid International Airports

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dc.authorid0000-0001-5658-7371en_US
dc.contributor.authorKoçak, Bahri Baran
dc.date.accessioned2023-10-19T10:39:17Z
dc.date.available2023-10-19T10:39:17Z
dc.date.issued2023en_US
dc.departmentDicle Üniversitesi, Sivil Havacılık Yüksek Okulu, Havacılık Yönetimi Bölümüen_US
dc.description.abstractManagers gain new insights into how operational benefits can be achieved. Forecasting problems for passenger flow in airports are gaining interest among marketing researchers, but comparison of stochastic optimisation methods via deep learning forecasts with search query data is not yet available in the aviation field. To fill this gap, the current study predicts the demand of Madrid airport demand with Google search query data using H2O deep learning method. The findings indicate that there is a long-term relationship between search queries and actual passenger demand. Besides, search queries “fly to madrid,” and “flights to madrid spain” were found to be the cause of the actual domestic air passenger demand in Madrid. Also, to determine the best forecasting accuracy, stochastic gradient descent (SGD) optimisers were used. Specifically, findings indicate that Adam is a better optimiser increasing forecasting accuracy for Madrid airports.en_US
dc.identifier.citationKoçak, B. B. (2023). Deep learning models for airport demand forecasting with google trends: A case study of Madrid International Airports. International Journal of Cyber Behavior, Psychology and Learning, 13(1), 1-13.en_US
dc.identifier.doi10.4018/IJCBPL.324086
dc.identifier.endpage13en_US
dc.identifier.issn2155-7136
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85172879956
dc.identifier.scopusqualityQ3
dc.identifier.startpage1en_US
dc.identifier.urihttps://www.igi-global.com/gateway/article/full-text-pdf/324086
dc.identifier.urihttps://hdl.handle.net/11468/12876
dc.identifier.volume13en_US
dc.indekslendigikaynakScopus
dc.institutionauthorKoçak, Bahri Baran
dc.language.isoenen_US
dc.publisherIGI Globalen_US
dc.relation.ispartofInternational Journal of Cyber Behavior, Psychology and Learning
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAirport demand forecastingen_US
dc.subjectBig data analyticsen_US
dc.subjectConsumer search behaviouren_US
dc.subjectH2O deep learningen_US
dc.subjectStochastic gradient descenten_US
dc.titleDeep learning models for airport demand forecasting with google trends: A case study of Madrid International Airportsen_US
dc.titleDeep learning models for airport demand forecasting with google trends: A case study of Madrid International Airports
dc.typeArticleen_US

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