# ICEEMDAN-VMD-FE-PACF-RF-TCN

Ozone concentration forecasting now runs on two-stage decomposition and two-scale feature selection. The raw series is first decomposed by ICEEMDAN, the most complex component IMF1 is decomposed again by VMD, and the remaining subsequences are reconstructed by fuzzy entropy; partial autocorrelation and random forest then select input dimensions before a temporal convolutional network predicts. On daily ozone data from Beijing and Shanghai, the combined model reaches MAE, RMSE and SMAPE of 0.53509, 0.73346 and 0.8433%, the best among four comparison experiments.

Ozone concentration forecasting now runs on two-stage decomposition and two-scale feature selection. The raw series is first decomposed by ICEEMDAN, the most complex component IMF1 is decomposed again by VMD, and the remaining subsequences are reconstructed by fuzzy entropy; partial autocorrelation and random forest then select input dimensions before a temporal convolutional network predicts. On daily ozone data from Beijing and Shanghai, the combined model reaches MAE, RMSE and SMAPE of 0.53509, 0.73346 and 0.8433%, the best among four comparison experiments.