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Published in:
Analysis and Optimization of Urban Energy Systems Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Predictive Analytics in Aviation Management: Passenger Arrival Prediction

Authors : Maximilian Moll, Thomas Berg, Simon Ewers, Michael Schmidt

Published in: Operations Research Proceedings 2019

Publisher: Springer International Publishing

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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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Metadata
Title
Predictive Analytics in Aviation Management: Passenger Arrival Prediction
Authors
Maximilian Moll
Thomas Berg
Simon Ewers
Michael Schmidt
Copyright Year
2020
Book
Operations Research Proceedings 2019

Print ISBN: 978-3-030-48438-5

Electronic ISBN: 978-3-030-48439-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-48439-2_81

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