A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction

A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction

Due to the strong propagation causality of delays between airports, this paper proposes a delay prediction model based on a deep graph neural network to study delay prediction from the perspective of an airport network. We regard airports as nodes of a graph network and use a directed graph network...

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Bibliographic Details
Main Authors:	Weili Zeng, Juan Li, Zhibin Quan, Xiaobo Lu
Format:	Article
Language:	English
Published:	Hindawi-Wiley 2021-01-01
Series:	Journal of Advanced Transportation
Online Access:	http://dx.doi.org/10.1155/2021/6638130

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