A Temporal Directed Graph Convolution Network for Traffic Forecasting Using Taxi Trajectory Data
Traffic forecasting plays a vital role in intelligent transportation systems and is of great significance for traffic management. The main issue of traffic forecasting is how to model spatial and temporal dependence. Current state-of-the-art methods tend to apply deep learning models; these methods...
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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI AG
2021-09-01
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| Edice: | ISPRS International Journal of Geo-Information |
| Témata: | |
| On-line přístup: | https://www.mdpi.com/2220-9964/10/9/624 |
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