## 3 Database and Data Collection
### Data Exploration  
The dataset used in this study contained 23,947 records after cleaning to remove missing values, and duplicates. A summary of the input variables is presented in Table 3 with the cutterhead torque having the largest range followed by the boring pressure. A pairwise correlation of the input variables presented in Table 4.  
tabreftabref:appslci-1041145-t004 shows that, apart from stroke speed and penetration rate, that have a strong positive correlation, the rest of the variables have very weak correlations. This shows that there are no concerns of multicollinearity. From Figure 5, the median cutterhead RPM decreases with decreasing rock mass competence. In a more competent rock mass, the penetration of the cutting tools into the rock mass is limited by the rock mass strength, therefore, the RPM of the cutterhead is higher than when rock mass is less competent (e.g., CII), where the cutting tool penetrates deeper. This is a possible explanation for the behavior of the cutterhead RPM observed in Figure 5.  
A close observation of Figure 6 shows a consistent decline in the median boring pressure from rock class A through rock class CII. This general decline in the applied pressure can be attributed to the decrease in the integrity of the rock mass from class A to CII. Massive competent rock, like rocks in class A, will require high excavation pressure for fragmentation than fractured rock such as those in class CII. In each rock type, the boring pressure is widely variable with a lot of outliers (Figure 6). This variability  
Figure 4: Tunnel zones during characterizations. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**TBM Parameter** & **Mean** & **Median** & **Minimum** & **Maximum** \\ \hline Boring pressure (N/mm\({}^{2}\)) & 56.35 & 47.10 & \(-\)5448.20 & 1155.80 \\ Cutterhead torque (kN-m) & 562.57 & 622.00 & \(-\)31,962 & 22,523.00 \\ Cutterhead thrust force (kN) & 9910.15 & 10,619.00 & 0.00 & 11,424.00 \\ Cutterhead RPM (rev/min) & 10.29 & 11.00 & 0.00 & 12.10 \\ Rate of penetration (m/h) & 2.30 & 2.10 & 0.00 & 107.80 \\ Stroke speed (mm/min) & 38.18 & 35.00 & 0.00 & 1797.00 \\ Gripper cylinder pressure (bar) & 301.67 & 306.00 & 0.00 & 691.00 \\ Pitching (\({}^{\circ}\)) & \(-\)0.06 & \(-\)0.09 & \(-\)0.52 & 1.26 \\ Average motor amps (A) & 138.79 & 138.00 & 0.00 & 427.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary statistics of the TBM data. stems from instantaneous heterogeneities that are encountered within one rock mass class. The variability is more pronounced in the first three classes and not as much in class CII. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**TBM Parameter** & **Boring Pressure** & **Cutterhead Torque** & **Cutterhead Thrust Force** & **Cutterhead RPM** & **Rate of Penetration** & **Stroke Speed** & **Gripper Cylinder Pressure** & **Pitching Motor Amps** \\ \hline Boring Pressure Cuttrehead torque Cuttrehead Cuttrehead Cuttrehead thrust force Cuttrehead Cuttrehead RPM Rate of Penetration & 1.00 0.21 & 1.00 1.00 0.28 1.00 0.26 0.28 0.26 0.28 0.26 0.28 0.26 0.28 0  
In terms of the rate of penetration or advancement rate, the median penetration rate increased from class A to class CI. This is intuitive since it is expected to be more difficult to advance in competent rock. CII however, shows an unexpected low penetration rate as shown in Figure 7. This may be attributed to other operation factors that accompany excavation in relatively weak rocks like class CII. The dataset had an obvious imbalance in the number of data points in each rock mass class (Figure 8, Table 5). This imbalance tends to affect the performance of classification models. Majority of the rock mass in the dataset were in class B. The number of rock mass data points in classes A and CI are comparable with only a small fraction of the dataset falling in class CII.