Probabilistic En Route Sector Traffic Demand Prediction Based on Quantile Regression Neural Network and Kernel Density Estimation

With the development of civil aviation in China, airspace congestion has become more and more serious and has gradually spread from airport terminal areas to en route networks. Traditionally, most prediction methods that obtain traffic flow data are based on the number of aircraft passing through an...

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Bibliografiske detaljer

Principais autores:	Wen Tian, Yining Zhang, Yuchen Li, Yixing Guo
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-02-01
Serier:	Applied Sciences
Fag:	air traffic demand prediction en route sector neural network quantile regression kernel density estimation probabilistic density
Online adgang:	https://www.mdpi.com/2076-3417/14/4/1515
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