An Explainable Spatio-Temporal Framework for Traffic Forecasting Using Graph-Based Features
Urban traffic prediction plays a critical role in improving transportation efficiency and supporting sustainability in smart cities. This study proposes an explainable spatio-temporal machine learning framework that integrates periodic temporal features with graph-based spatial representations. Temp...
Kaydedildi:
| Yazar: | |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IEEE
2026-01-01
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| Seri Bilgileri: | IEEE Access |
| Konular: | |
| Online Erişim: | https://ieeexplore.ieee.org/document/11601043/ |
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