Traffic flow prediction based on spatiotemporal encoder-decoder model.
To more effectively capture the periodic and dynamic changes in urban traffic flow and the spatiotemporal correlation of complex road networks, a new traffic flow prediction method, the Enhanced Spatiotemporal Graph Convolutional Network Encoder-Decoder Model (ESGCN-EDM), is proposed. The model achi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0321858 |
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