TFGCRN: Temporal–Frequency Graph Convolutional Recurrent Network for Incomplete Traffic Forecasting
Traffic forecasting is a crucial component that underpins an intelligent transportation system. Among the current mainstream forecasting algorithms, spatial–temporal graph neural networks (STGNNs), as the mainstream solution, have been used in traffic forecasting due to their ability to model spatia...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
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MDPI AG
2025-12-01
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| Serie: | Mathematics |
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| Accesso online: | https://www.mdpi.com/2227-7390/13/24/4003 |
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