## 4 Discussion  
### Analysis of the Influence of Shield Tunneling Features Based on SHAP Theory  
The improved Informer algorithm was employed as the input for the SHAP algorithm to investigate the effects of various features on surface settlement induced by shield tunneling. Figure 15 presents the SHAP values of the top 20 features with the highest contributions. The vertical axis lists the features in descending order of average SHAP values. The horizontal axis represents SHAP values. Positive SHAP values indicate that the feature tends to increase settlement, while negative values indicate a tendency to reduce settlement. The color gradient on the right represents the magnitude of the eigenvalues. The features on the vertical axis are arranged from top to bottom in descending order of importance; thus, shield thrust was identified as the most important feature influencing surface settlement. In addition, features such as the horizontal displacement of the shield head (HDSH) and cutterhead torque significantly impacted the prediction of surface settlement. Because shield thrust is the most important feature affecting settlement, a feature-dependence plot was drawn for shield thrust (Figure 16), where the color gradient represents the distribution of soil layer eigenvalues: blue corresponds to the silty soil layer, red corresponds to the silty clay layer, and purple corresponds to the composite soil layer. The type of soil layer largely determines the required thrust. For example, the silty clay layer, being denser, requires significantly more thrust than the silty soil layer during shield tunneling. Figure 14: Comparison with other prediction algorithms (about settlement). and 0.9, the disturbance to the soil layer was minimized, suggesting that the optimal thrust for these soil conditions is 0.8-0.9 times the maximum thrust. During the shield tunneling process, stable thrust can be maintained by appropriately controlling the cutterhead torque, advance rate, grouting pressure, and muck pressure and thereby reducing soil layer disturbance [38]. These four features are closely related to variations in thrust. To visualize these relationships, dependence plots were generated to illustrate the interactions between thrust and the cutterhead torque, advance rate, grouting pressure, and muck pressure, as shown in Figure 17.  
Figure 17a depicts the relationships between the cutterhead torque, thrust, and surface settlement. At low torque levels, the earth pressure balance was disrupted, increasing over-excavation risks [38]. However, high torque enhances soil mixing, reducing Type II-III settlement (Figure 4). Under the same thrust, the cutterhead torque and SHAP values showed a negative correlation. Figure 17b illustrates the relationship between the advance rate, thrust, and surface settlement. Low advance rates negatively impacted surface settlement, while high advance rates had a positive effect. A strong negative correlation was observed between the advance rate and thrust. Figure 17c,d show the relationships of the grouting pressure and muck pressure with the thrust and surface settlement, respectively. The grouting pressure and muck pressure had similar effects on the surface settlement. Muck pressure outside the optimal range (0.6-0.8) exacerbates ground loss: low pressure induces soil inflow, while high pressure fractures strata, escalating grout leakage and Type I-IV settlement [1; 6]. This suggests that increasing grouting and muck pressures during construction can significantly reduce soil  
Figure 17: Dependence plots for tunneling parameters: (**a**) cutterhead torque, (**b**) advance rate, (**c**) grouting pressure, and (**d**) muck pressure. layer disturbance. The correlation between thrust and these pressures was relatively weak, which agrees with actual construction conditions. Additionally, K-block misalignment (e.g., Positions 1-5) impedes segment ring closure, widening tail voids and aggravating Type IV settlement through uneven grout distribution [35].