Comparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Study

Basit Öğe Kaydı
dc.contributor.authorKoçak, Bahri Baran
dc.date.accessioned2024-04-24T19:13:25Z
dc.date.available2024-04-24T19:13:25Z
dc.date.issued2023
dc.departmentDicle Üniversitesi, Sivil Havacılık Yüksekokulu, Havacılık Yönetimi Bölümüen_US
dc.description.abstractWeb search queries become essential drivers to forecast air passenger demand for operational benefits. Scholars and marketing experts. Forecasting passenger demand is one of the most important marketing problems that experts frequently encounter, but there are very few studies in the literature using search queries. The main novelty of this study is to show that Destination Insight (DI) can be useful as an air passenger demand proxy in the UK. To prove this primary objective, this work uses several machine and deep learning multi-layer perceptron (MLP) methods based on a big-data framework. The findings indicate that DI is a crucial predictor of the UK air passenger demand. Besides, popular error metrics (RMSE, MAPE, MAD and AIC) were compared to find the best model in this study. Specifically, results indicate that MLP following feed forward neural networks works better for the UK air passenger market.en_US
dc.identifier.citationKoçak, B. B. (2023). Comparison of artificial intelligence techniques for The UK air passenger short-term demand forecasting: A destination insight study. Journal of aviation (Online), 7(3), 415-424.
dc.identifier.doi10.30518/jav.1351229
dc.identifier.endpage424en_US
dc.identifier.issn2587-1676
dc.identifier.issue3en_US
dc.identifier.startpage415en_US
dc.identifier.trdizinid1209296
dc.identifier.urihttps://doi.org/10.30518/jav.1351229
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/1209296
dc.identifier.urihttps://hdl.handle.net/11468/28597
dc.identifier.volume7en_US
dc.indekslendigikaynakTR-Dizin
dc.language.isoenen_US
dc.relation.ispartofJournal of aviation (Online)
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleComparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Studyen_US
dc.titleComparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Study
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Comparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting A Destination Insight Study.pdf
Boyut:
994.45 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası
İndir

Koleksiyon

TR-Dizin İndeksli Yayınlar Koleksiyonu