Author

Chao Huang

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Conference Open access 2026

Short Term Prediction of PM2.5 Concentration Based on PCA-LSTM-Random Forest

As the primary atmospheric pollutant, accurate short-term PM2.5 prediction is critical for air quality early warning and control. Existing methods are limited by high-dimensional feature redundancy, complex time-series dependence, and nonlinear correlations. This study constructs a PCA-LSTM-random forest integrated m...

Chao Huang · ITM Web of Conferences · 0 citations