## 3 Results and Discussion
### Predicted Results of RF  
Using the input variables listed in Table 3 and default parameters, the RF quantitative models of ash content, volatile matter and calorific value under different data set partitioning methods were established. The predicted results of the RF model are shown in Figure 4 and Table 5.  
It can be seen from Figure 4 and Table 5 that the prediction result of the RF model with the SPXY partitioning method is the best. The \(R^{2}\) of ash content is 0.9843, the _RMSE_ is 1.3303 and the mean relative error (_MRE_) is 7.47%. The \(R^{2}\) of volatile matter is 0.9801, _RMSE_ is 0.7843 and _MRE_ is 2.19%; the \(R^{2}\) of calorific value is 0.9844, _RMSE_ is 0.7324 and _MRE_ is 2.27%.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multirow{2}{*}{\begin{tabular}{c} **Partitioning** \\ **Method** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **R2** \\ **R2** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **RMSE** \\ **RMSE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **RMSE** \\ **RMSE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **RMSE** \\ **MAE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **MAE** \\ **MRE** \\ \end{tabular} } \\ \hline \multirow{2}{*}{\begin{tabular}{c} Ash \\ content \\ \end{tabular} } & RS & 0.9998 & 0.1608 & 4.6499 & 3.9341 & 0.2465 \\  & KS & 0.9981 & 0.6321 & 4.1393 & 3.2033 & 0.1655 \\  & SPXY & 0.9955 & 0.8824 & 2.1142 & 1.8288 & 0.0982 \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} Volatile \\ matter \\ \end{tabular} } & RS & 0.9999 & 0.0400 & 2.0314 & 1.3686 & 0.0577 \\  & KS & 0.9999 & 0.0399 & 1.2928 & 0.9098 & 0.0321 \\  & SPXY & 0.9999 & 0.0400 & 1.0895 & 0.8785 & 0.0327 \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Calorific \\ value \\ \end{tabular} } & RS & 0.9970 & 0.2029 & 1.5195 & 1.2466 & 0.0554 \\  & KS & 0.9999 & 0.0400 & 1.1252 & 0.8818 & 0.0387 \\  & SPXY & 0.9999 & 0.0397 & 1.2458 & 0.9676 & 0.0450 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The prediction results of the SVR model under different partitioning methods.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multirow{2}{*}{\begin{tabular}{c} **Partitioning** \\ **Method** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **R2** \\ **R2** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **RMSE** \\ **RMSE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **RMSE** \\ **RMSE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **MAE** \\ **MAE** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **MRE** \\ **MRE** \\ \end{tabular} } \\ \hline \multirow{2}{*}{\begin{tabular}{c} Ash \\ content \\ \end{tabular} } & RS & 0.9861 & 1.7693 & 3.2348 & 2.4389 & 0.1348 \\  & KS & 0.9886 & 1.6545 & 4.1274 & 3.1410 & 0.1585 \\  & SPXY & 0.9843 & 1.9235 & 1.3303 & 1.1760 & 0.0747 \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} Volatile \\ matter \\ \end{tabular} } & RS & 0.9818 & 0.8324 & 1.9561 & 1.4596 & 0.0515 \\  & KS & 0.9813 & 0.8541 & 1.3220 & 0.9841 & 0.0354 \\  & SPXY & 0.9801 & 0.9540 & 0.7843 & 0.6001 & 0.0219 \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Calorific \\ value \\ \end{tabular} } & RS & 0.9815 & 0.5646 & 1.8893 & 1.5568 & 0.0790 \\  & KS & 0.9849 & 0.6379 & 1.0612 & 0.7843 & 0.0354 \\  & SPXY & 0.9844 & 0.6381 & 0.7324 & 0.4941 & 0.0227 \\ \hline \hline \end{tabular}
\end{table}
Table 5: The prediction results of the RF model under different partitioning methods.  
Figure 4: _Cont_.