Predicting requested flight levels with machine learning
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/341211
Tipus de documentText en actes de congrés
Data publicació2020
EditorSingle European Sky ATM Research (SESAR)
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The objective of this paper is to present a machine learning approach for the prediction of the Requested Flight Level received during the pre-tactical phase of the Air Traffic Flow and Capacity Management process. A set of machine learning models are proposed in order to determine which Requested Flight Level is the most likely to be filed by an airspace user for a certain origin-destination pair. Results show that the proposed system outperforms the pre-tactical traffic forecasting approach currently used by the European Network Manager in 60% of the 14,465 origin-destination pairs considered in the study, reducing the error of the current solution by 4.8%.
CitacióMateos, M. [et al.]. Predicting requested flight levels with machine learning. A: SESAR Innovation Days. "10th SESAR Innovation Days: 7th of December-10th of December, 2020, virtual event". Single European Sky ATM Research (SESAR), 2020,
Altres identificadorshttps://www.sesarju.eu/sesarinnovationdays
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
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SIDs_2020_paper_62red.pdf | 95,02Kb | Visualitza/Obre |