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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6638130 |