Accurate prediction of urban metro ridership flows is crucial for effective transportation operation management and optimized individual travel planning. Addressing the complex spatio-temporal ...

In this paper, we propose a Dynamic Spatial-Temporal Graph Convolution Network (DSTGCN) for e-bike traffic flow forecasting. Specifically, we have designed an inter-road transition flow embedding ...

Let G be a directed graph such that every edge e of G is associated with a positive integer, called the index of e. Then G is called a network graph if, at every vertex v of G, the sum of the indices ...