Sutthiya Lertyongphati. Impact of external factors on air passenger demand prediction using machine learning. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Impact of external factors on air passenger demand prediction using machine learning
Abstract:
The aviation industry has seen considerable changes in recent years,
with multiple underlying factors influencing passenger demand.
This research delves into these external factors impacting air travel
demand in Thailand. By merging historical arrival data with diverse
datasets, the study aims to reveal how these factors affect
demand and enhance predictive models. Machine learning regression
models are utilized, focusing on Thailands historical inbound
passenger volume across three main regions. The research highlights
the importance of optimal time lags for search queries, given
passengers tendencies to search before traveling. Using a recursive
feature elimination process, the model was refined to include only
the most influential variables. Correlation analyses reinforced these
conclusions, and by incorporating location-specific Google Trend
queries, prediction precision was notably improved. The methodology
not only affirms the significant role of external factors in
shaping air travel demand but also demonstrates its broader application
in the tourism sector. This study provides key insights for
improved demand forecasting in Thailands tourism and aviation
sectors
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2023
Modified:
2025-03-03
Issued:
2025-03-03
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BibliograpyCitation :
In King Mongkut's University of Technology Thonburi. The 13th International Conference on Advances in Information Technology (IAIT 2023) (Article 8). Bangkok : King Mongkut's University of Technology Thonburi