Abstract Accurate traffic flow forecasting Shoes is a critical component in intelligent transportation systems.However, most of the existing traffic flow prediction algorithms only consider the prediction under normal conditions, but not the influence of weather attributes on the prediction results.This study applies a hybrid deep learning model based on multi feature fusion Defrost Fuse to predict traffic flow considering weather conditions.A comparison with other representative models validates that the proposed spatial‐temporal fusion graph convolutional network (STFGCN) can achieve better performance.