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Structure‐Enhanced Graph Learning Approach for Traffic Flow and Density Forecasting

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Proposed SGL4TF model improves traffic flow and density forecasting, highlighting AI's role in ITS.

The SGL4TF model significantly enhances traffic forecasting accuracy by integrating graph convolutional networks.
Extensive experiments on real-world datasets show that the SGL4TF model outperforms existing state-of-the-art traffic forecasting techniques.
Using a seq2seq framework, the model effectively captures long-term temporal dependencies in traffic data.
The approach addresses challenges in preserving structural and topological features, leading to better prediction outcomes.

Phu Pham (2025) studied this question.

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