Rongsheng Wei

Application of stacked Transformer-XGBoost model and SHAP interpretability in air quality index prediction in Linfen City

Summary This study proposes a stacked Transformer-XGBoost framework with Shapley Additive Explanations (SHAP) interpretability to improve Air Quality Index prediction in Linfen City, a heavily industrialized region characterized by complex pollution dynamics and strong seasonal variability. The model combines Transform...