A framework for continual learning in real-time traffic forecasting utilizing spatial–temporal graph convolutional recurrent networks
Abstract Traffic flow prediction is essential for enhancing urban mobility and facilitating effective transportation systems. The rapid increase in traffic data, along with the inherently dynamic characteristics of urban traffic, poses considerable challenges for traditional Machine Learning (ML) mo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-025-02049-7 |
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