Yi-Meng Zhu

Federated Learning Approach for Multi-Regional Traffic Flow Prediction

Experiments on controlled synthetic data and the Q-Traffic real-world dataset demonstrate that the proposed framework improves predictive accuracy, cross-client stability, and robustness under heterogeneous federated traffic scenarios.