## 5 Results
### Feature Selection
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & **OT** & **DW** & **HD** & **WON** & **AQI** & **PM2.5** & **PM10** & **SO2** & **NO2** & **CO** \\ \hline
**OT** & 1 & 0.23 & 0.79 & 0.22 & 0.06 & 0.06 & 0.07 & 0.02 & 0.08 & 0.08 \\
**DW** & 0.23 & 1 & 0 & 0.79 & 0.29 & 0.28 & 0.34 & 0.13 & 0.36 & 0.4 \\
**HD** & 0.79 & 0 & 1 & 0.11 & 0.05 & 0.07 & 0.09 & 0.05 & 0.14 & 0.12 \\
**WON** & 0.22 & 0.79 & 0.11 & 1 & 0.13 & 0.2 & 0.25 & 0.19 & 0.25 & 0.35 \\
**AQI** & 0.06 & 0.29 & 0.05 & 0.13 & 1 & 0.79 & 0.95 & 0.3 & 0.69 & 0.8 \\
**PM2.5** & 0.06 & 0.28 & 0.07 & 0.2 & 0.79 & 1 & 0.7 & 0.46 & 0.8 & 0.88 \\
**PM10** & 0.07 & 0.34 & 0.09 & 0.25 & 0.95 & 0.7 & 1 & 0.37 & 0.67 & 0.8 \\
**SO2** & 0.02 & 0.13 & 0.05 & 0.19 & 0.3 & 0.46 & 0.37 & 1 & 0.46 & 0.5 \\
**NO2** & 0.08 & 0.36 & 0.14 & 0.25 & 0.69 & 0.8 & 0.67 & 0.46 & 1 & 0.91 \\
**CO** & 0.08 & 0.4 & 0.12 & 0.35 & 0.8 & 0.88 & 0.8 & 0.5 & 0.91 & 1 \\
**O3** & \(-\)0.18 & \(-\)0.25 & 0.07 & \(-\)0.15 & \(-\)0.35 & \(-\)0.53 & \(-\)0.35 & \(-\)0.34 & \(-\)0.36 & \(-\)0.47 \\
**W** & \(-\)0.02 & \(-\)0.17 & 0 & \(-\)0.2 & 0.31 & 0.51 & 0.16 & 0.15 & 0.23 & 0.3 \\
**WS** & 0.11 & \(-\)0.04 & 0.1 & 0.02 & \(-\)0.02 & 0.13 & \(-\)0.01 & 0.48 & 0.04 & 0 \\
**TEM** & \(-\)0.39 & \(-\)0.07 & \(-\)0.38 & \(-\)0.06 & 0.01 & 0.02 & \(-\)0.06 & \(-\)0.36 & 0 & 0.04 \\
**RHU** & 0.41 & 0.13 & 0.34 & 0.19 & 0.08 & 0.15 & 0.11 & \(-\)0.11 & 0.18 & 0.2 \\
**PRE** & 0.02 & \(-\)0.02 & 0 & \(-\)0.02 & \(-\)0.04 & \(-\)0.03 & \(-\)0.05 & \(-\)0.05 & \(-\)0.06 & \(-\)0.03 \\
**SSD** & 0.06 & 0.22 & 0 & 0.18 & \(-\)0.09 & \(-\)0.29 & 0.07 & 0 & 0.19 & 0.03 \\
**TG** & \(-\)0.23 & \(-\)0.03 & \(-\)0.13 & \(-\)0.04 & \(-\)0.09 & \(-\)0.14 & \(-\)0.14 & \(-\)0.56 & \(-\)0.11 & \(-\)0.07 \\
**VIS** & \(-\)0.27 & \(-\)0.18 & \(-\)0.17 & \(-\)0.28 & \(-\)0.04 & \(-\)0.29 & \(-\)0.06 & \(-\)0.24 & \(-\)0.35 & \(-\)0.34 \\
**TX** & 0.52 & 0.06 & 0.5 & 0.01 & 0.01 & 0.02 & 0 & \(-\)0.04 & 0.04 & 0.02 \\ \hline  & **O3** & **W** & **WS** & **TEM** & **RHU** & **PRE** & **SSD** & **TG** & **VIS** & **TX** \\ \hline
**OT** & \(-\)0.18 & \(-\)0.02 & 0.11 & \(-\)0.39 & 0.41 & 0.02 & 0.06 & \(-\)0.23 & \(-\)0.27 & 0.52 \\
**DW** & \(-\)0.25 & \(-\)0.17 & \(-\)0.04 & \(-\)0.07 & 0.13 & \(-\)0.02 & 0.22 & \(-\)0.03 & \(-\)0.18 & 0.06 \\
**HD** & 0.07 & 0 & 0.1 & \(-\)0.38 & 0.34 & 0 & 0 & \(-\)0.13 & \(-\)0.17 & 0.5 \\
**WON** & \(-\)0.15 & \(-\)0.2 & 0.02 & \(-\)0.06 & 0.19 & \(-\)0.02 & 0.18 & \(-\)0.04 & \(-\)0.28 & 0.01 \\
**AQI** & \(-\)0.35 & 0.31 & \(-\)0.02 & 0.01 & 0.08 & \(-\)0.04 & \(-\)0.09 & \(-\)0.09 & \(-\)0.04 & 0.01 \\
**PM2.5** & \(-\)0.53 & 0.51 & 0.13 & 0.02 & 0.15 & \(-\)0.03 & \(-\)0.29 & \(-\)0.14 & \(-\)0.29 & 0.02 \\
**PM10** & \(-\)0.35 & 0.16 & \(-\)0.01 & \(-\)0.06 & 0.11 & \(-\)0.05 & 0.07 & \(-\)0.14 & \(-\)0.06 & 0 \\
**SO2** & \(-\)0.34 & 0.15 & 0.48 & \(-\)0.36 & \(-\)0.11 & \(-\)0.05 & 0 & \(-\)0.56 & \(-\)0.24 & \(-\)0.04 \\
**NO2** & \(-\)0.36 & 0.23 & 0.04 & 0 & 0.18 & \(-\)0.06 & 0.19 & \(-\)0.11 & \(-\)0.35 & 0.04 \\
**CO** & \(-\)0.47 & 0.3 & 0 & 0.04 & 0.2 & \(-\)0.03 & 0.03 & \(-\)0.07 & \(-\)0.34 & 0.02 \\
**O3** & 1 & \(-\)0.02 & 0.02 & \(-\)0.06 & \(-\)0.13 & \(-\)0.08 & 0.27 & \(-\)0.02 & 0.17 & \(-\)0.02 \\
**W** & \(-\)0.02 & 1 & 0.06 & 0.04 & 0.08 & \(-\)0.03 & \(-\)0.51 & \(-\)0.07 & \(-\)0.19 & \(-\)0.05 \\
**WS** & 0.02 & 0.06 & 1 & \(-\)0.53 & \(-\)0.2 & \(-\)0.07 & \(-\)0.14 & \(-\)0.68 & \(-\)0.02 & 0.01 \\
**TEM** & \(-\)0.06 & 0.04 & \(-\)0.53 & 1 & \(-\)0.22 & 0.03 & \(-\)0.08 & 0.8 & 0.13 & \(-\)0.2 \\
**RHU** & \(-\)0.13 & 0.08 & \(-\)0.2 & \(-\)0.22 & 1 & 0.11 Then, all data are proceeded through by the One-Hot Encoder function in the scikit-learn. preprocessing library. An instance of the DW indicator is shown in Figure 2.  
After the encoding of indicators in Table 5, the dimension of the dataset was expanded to 58. Additionally, the first 23 days of November 2016 are taken as the training set, with the other seven days as the testing set in this study.