Dynamic Spatio-Temporal Graph Fusion Convolutional Network for Urban Traffic Prediction
Urban traffic prediction is essential for intelligent transportation systems. However, traffic data often exhibit highly complex spatio-temporal correlations, posing challenges for accurate forecasting. Graph neural networks have demonstrated an outstanding ability in capturing spatial correlations...
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI AG
2023-08-01
|
| Collection: | Applied Sciences |
| Sujets: | |
| Accès en ligne: | https://www.mdpi.com/2076-3417/13/16/9304 |
| Tags: |
Pas de tags, Soyez le premier à ajouter un tag!
|