A Bidirectional Gated Recurrent Unit and Temporal Convolutional Network With a Self-Attention Mechanism to Improve Traffic Flow Prediction Performance
An effective temporal modeling approach is crucial for improving traffic flow prediction accuracy. Traditional traffic flow prediction methods have certain limitations in capturing long-term dependencies and enhancing computational efficiency. This is especially true when dealing with long-sequence...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10978011/ |
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