High-dimensional population inflow time series forecasting via an interpretable hierarchical transformer

•A deep learning framework is introduced for nationwide population inflow forecasting.•Temporal dynamics are captured via Transformer with local enhancements.•External effects from various factors with different dimensions are fused and selected.•Models are interpreted from static and temporal aspects via built-in parameters.