Abstract
Due to increasing passenger and flight numbers, airports need to plan and schedule carefully to avoid wasting their resources, but also congestion and missed flights. In this paper, we present a deep learning framework for predicting the number of passengers arriving at an airport within a 15-min interval. To this end, a first neural network predicts the number of passengers on a given flight. These results are then being used with a second neural network to predict the number of passengers in each interval.
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Moll, M., Berg, T., Ewers, S., Schmidt, M. (2020). Predictive Analytics in Aviation Management: Passenger Arrival Prediction. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_81
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DOI: https://doi.org/10.1007/978-3-030-48439-2_81
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