Dynamic feature-adaptive representation learning for spatiotemporal air pollution forecasting
FAST (Feature-Adaptive Selection and Transformation), a novel approach for dynamic feature selection for spatiotemporal air quality forecasting, improves forecasting accuracy and interpretability, outperforms traditional methods across major Indian cities and forecasting horizons, and offers scalable support for data d...