Graph convolution networks based on adaptive spatiotemporal attention for traffic flow forecasting
Abstract Traffic flow is the most direct indicator of traffic conditions, and accurate prediction of traffic flow is a key challenge for scholars in the field of intelligent transportation. However, traffic flow displays significant nonlinearity, dynamic changes, spatiotemporal dependencies, and mos...
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| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Nature Portfolio
2025-03-01
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| Серія: | Scientific Reports |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1038/s41598-025-88706-w |
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