Short-Term Online Forecasting for Passenger Origin–Destination (OD) Flows of Urban Rail Transit: A Graph–Temporal Fused Deep Learning Method
Predicting short-term passenger flow accurately is of great significance for daily management and for a timely emergency response of rail transit networks. In this paper, we propose an attention-based Graph–Temporal Fused Neural Network (GTFNN) that can make online predictions of origin–destination...
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| Autors principals: | , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2022-10-01
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| Col·lecció: | Mathematics |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2227-7390/10/19/3664 |
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