# Research on Pressure Exertion Prediction in Coal Mine Working Faces Based on Data-Driven Approaches
## 3 Results and Discussion
### Pressure Exertion Prediction Based on Pre-Trained Models  
In practical applications, the support resistance data for the next 30 cycles are first predicted based on the support resistance data from the previous 50 cycles. Then, the predicted support resistance data for the 30 cycles are input into the pressure label classification model. Based on the classification results, the input support resistance data for the pressure exertion characteristic parameters are extracted to obtain the required parameters. The above is the model training and evaluation result based on actual measured support resistance. In this section, the above model is used as a pre-trained model to simulate practical application scenarios and evaluate the model's prediction performance. The simulation scenario is based on the historical support resistance data collected from nine working faces. First, the support resistance data are predicted by sequentially increasing the support cycle number. The input data consist of the support resistance data from the previous 50 cycles, and the output data are the support resistance data for the next 30 cycles. If there are missing or abnormal values in the support resistance data for these 80 cycles, they are not included in the analysis sample. When constructing the support resistance feature matrix, the support resistance data from the two cycles before and after the target cycle is required. Therefore, in practical applications, only the support resistance data for the next 28 cycles can be predicted. This paper also includes the pressure exertion status of the current support cycle in the analysis, as the characteristics of the pressure exertion also need to be predicted if the current cycle is under pressure exertion. Therefore, a total of 29 support cycles' pressure exertion characteristics need to be analyzed. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Input**} & \multicolumn{2}{c}{**Dynamic Pressure**} & \multicolumn{2}{c}{**Error of Maximum**} & \multirow{2}{*}{**Error of Duration**} & \multicolumn{2}{c}{**Accuracy for Pressure**} \\  & \multicolumn{2}{c}{**Coefficient**} & \multicolumn{2}{c}{**Resistance**} & & & \multicolumn{2}{c}{**Exertion Type**} \\ \cline{2-9}  & **Epochs** & **MAE** & **Epochs** & **MAE/kN** & **Epochs** & **MAE/Cycles** & **Epochs** & **Acc/\%** \\ \hline “Third stage” & 513 & 0.23 & 221 & 1137.51 & 144 & 10.45 & 204 & 76.14 \\ \hline “Second stage” & 12 & 0.24 & 34 & 977.93 & 963 & 11.58 & 813 & 78.32 \\ \hline “First stage” & & & & & & & & \\ +”Second stage” & 927 & 0.17 & 48 & 810.93 & 32 & 9.96 & 73 & 92.35 \\ \hline “Second stage” & 324 & 0.23 & 37 & 947.05 & 61 & 23.92 & 608 & 58.65 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Statistics of optimal training results under different input information scenarios. When predicting the pressure exertion characteristic parameters, the predicted support resistance data for 30 cycles are input into the pressure label classification model to obtain the pressure labels for those 30 cycles. The pressure labels for the last 28 cycles are then concatenated with the historical cycle pressure labels, and the maximum value for each cycle is taken to obtain the periodic pressure exertion characteristic distribution curve. The last 29 cycles of the periodic pressure exertion distribution curve are the 29 cycles that need to be analyzed. If any of these 29 cycles are under pressure exertion, the start cycle of the pressure exertion, as well as the start and end cycle numbers for the three stages of the pressure exertion, can be obtained from the curve. Here, only pressure exertions that include three complete stages are analyzed. When data for three complete stages are not available, the characteristic value for that pressure exertion is defined as \(-1\). Next, the predicted pressure exertions are matched with the actual pressure exertions. If the difference in the starting cycle between the two is less than two cycles, it indicates that the pressure exertion has been accurately predicted.