# Research on the Prediction Model of Blasting Vibration Velocity in the Dahuangshan Mine
## 4 Result and Discussion  
### Analysis of the Learning Results  
Import the test samples into the trained EWT-XGBoost blasting vibration velocity prediction model for prediction. The comparison of the test samples and prediction results is shown in Table 5:  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \(\rho\)/(kg/m\({}^{3}\)) & \(D\)/(m/s) & \(G\)/(MPa) & \(A\)/(GPa) & \(B\)/(Gpa) & \(R_{1}\) & \(R_{2}\) & \(\omega\) & \(E\)/(MPa) \\ \hline
1100 & 3600 & 3500 & 214.4 & 0.182 & 4.2 & 0.9 & 0.15 & 4 192 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of the No. 2 rock emulsion explosive.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\rho\)/(kg/m\({}^{3}\)) & \(D\)/(m/s) & \(G\)/(MPa) & \(A\)/(GPa) & \(B\)/(Gpa) & \(R_{1}\) & \(R_{2}\) & \(\omega\) & \(E\)/(MPa) \\ \hline
1100 & 3600 & 3500 & 214.4 & 0.182 & 4.2 & 0.9 & 0.15 & 4 192 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Parameters of the No. 2 rock emulsion explosive.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \(\rho\)/(kg\(\cdot\)cm\({}^{-3}\)) & \(G\)/(MPa) & \(A\) & \(B\) & \(C\) & \(N\) & \(f_{c}\)/(MPa) \\ \hline
1.8 & 6543 & 0.55 & 1.77 & 0.0097 & 0.77 & 50 \\ \hline \hline \(T\)/(MPa) & \(\epsilon_{0}\)/(s\({}^{-1}\)) & \(\epsilon_{f,\min}\) & \(S_{\max}\) & \(P_{c}\)/(MPa) & \(U_{c}\) & \(P_{L}\)/(MPa) \\ \hline
3.3 & \(1\times 10^{-6}\) & 0.01 & 17 & 17 & 0.00253 & 2500 \\ \hline \hline \(U_{\text{L}}\) & \(D_{1}\) & \(D_{2}\) & \(K_{1}\)/(MPa) & \(K_{2}\)/(MPa) & \(K_{3}\)/(MPa) & \(f\)s \\ \hline
0.38 & 0.04 & 1 & 3100 & 6000 & 8400 & 0.035 \\ \hline \hline \end{tabular} \(\rho\): mass density, \(G\): shear modulus, \(A\): normalized cohesive strength, \(B\): normalized pressure hardening, \(C\): strain rate coefficient, \(N\): pressure hardening exponent, \(f_{c}\): quasi-static uniaxial compressive strength, \(T\): maximum tensile hydrostatic pressure, \(\epsilon_{0}\): quasi-static threshold strain rate, \(\epsilon_{t,\min}\): amount of plastic strain before fracture, \(S_{\max}\): normalized maximum strength, \(P_{c}\): crushing pressure, \(U_{c}\): crushing volumetric strain, \(P_{L}\): locking pressure, \(U_{L}\): locking volumetric strain, \(D_{1}\): damage constant, \(D_{2}\): damage constant, \(K_{1}\): pressure constant, \(K_{2}\): pressure constant, \(K_{3}\): pressure constant, \(f\)s: failure type.  
\end{table}
Table 2: HJC model parameters of the tuff material.  
It can be seen from the Figure 6 that the maximum relative error of the prediction result of the blasting vibration velocity of the EWT-XGBoost model is 7.69%, which is less than the maximum relative error of the XGBoost model (11.8%). The average relative error of the prediction results of the EWT-XGBoost model can be obtained by statistical calculation of the relative error, which yields 2.03%, which is less than the average relative error of the prediction results of the XGBoost model (4.49%). Formula 8 is used to calculate the root mean square error of the two models. According to the calculation, it can be concluded that the root mean square error of the prediction result of the EWT-XGBoost model is 0.0035, which is smaller than the root mean square error of the prediction result of the XGBoost model, which is 0.0836. Therefore, in terms of predicting the blasting vibration velocity The EWT-XGBoost model is better than the XGBoost model.