Graph neural network for traffic forecasting: A survey
Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have been extensively applied in traffic forecasting problems to model spatial and temporal dependencies. In recent years...
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Published in | Expert systems with applications Vol. 207; p. 117921 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
30.11.2022
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Subjects | |
Online Access | Get full text |
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