Accurate traffic flow prediction is a crucial step in building an intelligent transportation system, and it is of great significance for alleviating urban traffic congestion and optimizing travel routes. Due to the complex spatial topology of the transportation network and the highly nonlinear temporal dynamic characteristics of the flow data, traditional prediction methods are difficult to fully capture the inherent spatio-temporal dependencies. Therefore, this paper proposes a traffic flow prediction model based on variant hybrid multi-hop graph convolution. Firstly, by introducing a multi-hop graph convolution operator, the model explicitly aggregates the spatial information of multiple-o... More >