Predicting Airplane Go-Arounds Using Machine Learning and Open-Source Data

Predicting Airplane Go-Arounds Using Machine Learning and Open-Source Data

Go-arounds (GAs) are standard air traffic control procedures during which aircraft approach a runway but do not land. The incidence of a GA can subsequently affect the workload of flight crews and air traffic controllers, and might impact an airport runway’s throughput capacity. In this study, two d...

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Bibliographic Details
Main Authors: Benoit Figuet, Raphael Monstein, Manuel Waltert, Steven Barry
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Proceedings
Subjects:
OpenSky network
go-around
prediction
machine learning
generalized additive model
ADS-B
Online Access:https://www.mdpi.com/2504-3900/59/1/6

Internet

https://www.mdpi.com/2504-3900/59/1/6

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