An MLP achieves the best PM2.5 nowcasting performance in Beijing, while stability selection identifies CO, NO2, PM10, and the first-order PM2.5 lag as a robust core variable set across Lasso and Elastic Net.
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Nowcasting PM2.5 in Beijing Using Synchronous Covariates and Lagged Features: Model Comparison and Variable Selection Stability
An MLP achieves the best PM2.5 nowcasting performance in Beijing, while stability selection identifies CO, NO2, PM10, and the first-order PM2.5 lag as a robust core variable set across Lasso and Elastic Net.