A model for forecasting flight advance booking demand with competition effect

Liangyu Chen; Zhenhua Wu; Wenguo Yang; Suixiang Gao

doi:10.1117/12.3032987

5 July 2024 A model for forecasting flight advance booking demand with competition effect

Liangyu Chen, Zhenhua Wu, Wenguo Yang, Suixiang Gao

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131846P (2024) https://doi.org/10.1117/12.3032987
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Increasing competition and implementation of revenue management strategies in the airline industry have boosted accurate demand forecasting to maximize revenue. While most previous demand forecasting studies have focused on final booking demand of flights, this study develops a novel Transformer-based deep learning model to forecast flight advance bookings at daily granularity, named Flightformer. The proposed model considers the competition effect from other flights on the same route and determines the hyperparameters with Bayesian optimization. Subsequently, real flight advance booking data for nearly four years are used to evaluate the model performance. The results of the comparative experiment and ablation study show that Flightformer significantly outperforms the baseline and variant models. Moreover, the transferability of Flightformer on the other new route is examined.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liangyu Chen, Zhenhua Wu, Wenguo Yang, and Suixiang Gao "A model for forecasting flight advance booking demand with competition effect", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131846P (5 July 2024); https://doi.org/10.1117/12.3032987

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