Traffic flow data has strong temporal and spatial correlation. The traffic flow in the previous moment will affect the traffic flow in the next moment, and the traffic flow in the upstream and downstream will affect each other in space. . In order to alleviate traffic congestion and improve the accuracy of traffic flow prediction, this paper proposes a combined traffic flow prediction model C GCN based on graph convolution. product to extract the temporal features of the traffic flow. The experimental results show that the prediction effect of the C- GCN combination prediction model is better.