## 4 Experimental Results and Discussion
### Estimating Results
\begin{table}
\begin{tabular}{l l l l l l l l l l} \hline \hline
**Station** & **Network** & **RMSE** & **MSE** & **MAE** & **SMAPE** & **NAE** & **R2** & **IA** & **Time** \\ \hline \multirow{8}{*}{1002} & LSTM & 17.100 & 292.438 & 11.141 & 29.090 & 0.049 & 0.874 & 0.966 & 25.19 s \\  & GRU & 15.053 & 226.618 & 9.092 & 20.795 & 0.039 & 0.903 & 0.975 & 23.71 s \\  & SRU & 15.236 & 232.158 & 9.184 & 21.066 & 0.041 & 0.900 & 0.974 & 24.49 s \\  & TCN & 15.577 & 242.661 & 9.626 & 20.725 & 0.043 & 0.896 & 0.973 & 62.88 s \\  & Gaussian-TCN & 15.370 & 236.251 & 9.149 & 20.088 & 0.039 & 0.898 & 0.973 & 90.53 s \\  & GL-TCN & 16.172 & 261.561 & 9.955 & 20.791 & 0.042 & 0.888 & 0.972 & 68.26 s \\  & DD-TCN & 15.752 & 248.132 & 9.488 & 20.085 & 0.042 & 0.893 & 0.973 & 119.98 s \\  & D-TCN & 16.111 & 259.579 & 10.736 & 23.352 & 0.047 & 0.888 & 0.970 & 84.22 s \\  & ST-TCN & 18.352 & 341.812 & 12.281 & 35.152 & 0.285 & 0.668 & 0.913 & 67.38 s \\  & DMSnet & 16.622 & 280.291 & 11.371 & 28.682 & 0.210 & 0.824 & 0.957 & 17391 s \\  & LR-TCN & 15.454 & 238.839 & 9.637 & 20.862 & 0.042 & 0.897 & 0.974 & 59.99 s \\  & GRU-LR-TCN & 14.837 & 220.158 & 9.024 & 19.813 & 0.039 & 0.905 & 0.975 & 86.24 s \\ \hline \multirow{8}{*}{1003} & LSTM & 19.620 & 384.953 & 11.154 & 20.505 & 0.037 & 0.842 & 0.957 & 21.64 s \\  & GRU & 18.934 & 358.513 & 10.625 & 17.873 & 0.035 & 0.853 & 0.961 & 22.77 s \\  & SRU & 18.919 & 357.954 & 10.601 & 18.075 & 0.035 & 0.853 & 0.961 & 19.83 s \\  & TCN & 18.822 & 354.279 & 10.820 & 17.985 & 0.036 & 0.855 & 0.959 & 70.24 s \\  & Gaussian-TCN & 19.096 & 364.671 & 10.901 & 17.524 & 0.036 & 0.850 & 0.961 & 81.81 s \\  & GL-TCN & 18.834 & 354.727 & 10.503 & 17.250 & 0.035 & 0.855 & 0.962 & 68.13 s \\  & DD-TCN & 18.857 & 355.611 & 10.609 & 16.955 & 0.035 & 0.854 & 0.961 & 119.54 s \\  & D-TCN & 19.049 & 362.886 & 11.132 & 17.706 & 0.037 & 0.851 & 0.960 & 77.66 s \\  & ST-TCN & 19.643 & 390.855 & 18.281 & 20.117 & 0.233 & 0.721 & 0.902 & 65.41 s \\  & DMSnet & 18.845 & 360.126 & 13.345 & 19.091 & 0.190 & 0.736 & 0.932 & 16974 s \\  & LR-TCN & 18.695 & 349.530 & 10.556 & 16.162 & 0.035 & 0.857 & 0.962 & 57.34 s \\  & GRU-LR-TCN & 18.746 & 351.422 & 10.530 & 16.417 & 0.035 & 0.856 & 0.962 & 85.42 s \\ \hline \multirow{8}{*}{1023} & LSTM & 18.692 & 349.421 & 11.534 & 34.034 & 0.042 & 0.867 & 0.965 & 22.04 s \\  & GRU & 17.832 & 317.985 & 10.132 & 19.563 & 0.039 & 0.879 & 0.968 & 24.32 s \\  & SRU & 17.830 & 317.910 & 10.531 & 19.585 & 0.041 & 0.879 & 0.968 & 21.09 s \\  & TCN & 18.586 & 345.452 & 11.003 & 20.384 & 0.035 & 0.869 & 0.964 & 63.52 s \\  & Gaussian-TCN & 18.607 & 346.228 & 11.003 & 23.537 & 0.037 & 0.868 & 0.966 & 88.23 s \\  & GL-TCN & 18.317 & 335.532 & 11.343 & 19.693 & 0.043 & 0.872 & 0.967 & 69.91 s \\  & DD-TCN & 18.067 & 326.416 & 10.741 & 20.532 & 0.041 & 0.876 & 0.968 & 119.86 s \\  & D-TCN & 18.130 & 328.718 & 10.910 & 20.068 & 0.041 & 0.875 & 0.967 & 88.71 s \\  & ST-TCN & 19.628 & 411.201 & 15.056 & 29.230 & 0.306 & 0.665 & 0.885 & 63.72 s \\  & DMSnet & 18.662 & 358.742 & 12.469 & 26.936 & 0.194 & 0.801 & 0.943 & 16810 s \\  & LR-TCN & 18.200 & 331.270 & 10.980 & 18.917 & 0.040 & 0.874 & 0.968 & 54.65 s \\  & GRU-LR-TCN & 17.878 & 319.646 & 10.630 & 21.768 & 0.041 & 0.878 & 0.969 & 83.10 s \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Experiment on the generalization of regression estimation of PM\({}_{2.5}\) concentration.