Dynamic spatiotemporal graph network for traffic accident risk prediction
Traffic accidents remain major public safety concerns, often causing severe injuries, deaths, and economic costs, especially in rapidly urbanizing areas. Accurate traffic accident risk prediction is crucial for developing effective strategies to reduce accidents and enhance urban mobility. However,...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2025.2514330 |
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