Xu Li

EADGN: an event-adaptive dynamic graph network for robust traffic flow forecasting under anomalous conditions

Traffic flow forecasting across diverse scenarios is critical yet challenging. Existing methods often exhibit substantial performance degradation under anomalous conditions, such as traffic accidents, because of severe spatiotemporal disruptions. To address this limitation, we pr...