Jingjia Luo

MADGCN: A Meteorology-Aware Spatio-Temporal Graph Convolution Network for Long-Term Air Pollution Forecasting

Air quality forecasting has attracted increasing attention as global air pollution worsens. Spatiotemporal graph neural networks have become a leading paradigm, thanks to their ability to capture complex spatial and temporal dynamics in Air Quality Index (AQI) data. However, existing methods remain limited by weak mode...