## 3 Results
### Consolidation Analysis Results  
The relationship between soil parameters and settlement value was evaluated using correlation analysis, and the results presented in Table 7 show that there is a significant negative correlation (\(\rho=-0.402\), \(p<0.05\)) between excavation level and slump, indicating that deeper excavation levels may cause a decrease in slump. In contrast, other parameters such as unit weight, water content and cohesion show weak and insignificant correlations with slump, suggesting that they have limited direct effect under the analysed conditions. Significant correlations at the 0.05 level were determined between groundwater level and sieve No. 10 (\(p=-0.642,p<0.05\)) and unit weight and sieve No. 10 (\(p=0.632,p<0.05\)), reflecting their interaction in indirectly affecting soil behaviour. These results reveal the complexity of the consolidation process, where individual parameters may not have a direct effect on settlement but may act together with other factors. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multirow{2}{*}{**Settlement**} & \multirow{2}{*}{** \begin{tabular}{c} **Excavation** \\ **Level** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Groundwater** \\ **Level** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Unit** \\ **Level** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Water** \\ **Weight** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Sieve** \\ **Content** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Sieve** \\ **No. 10** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Sieve** \\ **No. 200** \\ \end{tabular}  } & \multirow{2}{*}{\ \begin{tabular}{c} **Sieve** \\ **Argle** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Cubesion** \\ **Coefficient** \\ \end{tabular}  } \\ \hline \multirow{3}{*}{Settlement} & Correlation & 1 & \(-0.402\)* & \(0.004\) & \(-0.240\) & \(-0.052\) & \(-0.303\) & \(-0.310\) & \(-0.002\) & \(0.334\) \\ \cline{2-11}  & Sig. & & \(0.046\) & \(0.986\) & \(0.247\) & \(0.806\) & \(0.338\) & \(0.132\) & \(0.993\) & \(0.150\) \\ \cline{2-11}  & N & 27 & 27 & 27 & 27 & 27 & 27 & 27 & 27 & 27 \\ \hline \multirow{3}{*}{Excavation Level} & Correlation & \(-0.402\)* & \(1\) & \(0.067\) & \(0.047\) & \(-0.121\) & \(-0.347\) & \(0.145\) & \(0.036\) & \(-0.094\) \\ \cline{2-11}  & Sig. & \(0.046\) & & \(0.740\) & \(0.816\) & \(0.547\) & \(0.270\) & \(0.471\) & \(0.864\) & \(0.676\) \\ \cline{2-11}  & N & 27 & 27 & 27 & 27 & 27 & 27 & 27 & 27 & 27 \\ \hline \multirow{3}{*}{Ground water} & Correlation & \(0.004\) & \(0.067\) & \(1\) & \(-0.457\)* & \(-0.094\) & \(-0.642\)* & \(0.323\) & \(-0.225\) & \(0.190\) \\ \cline{2-11}  & Sig & \(0.986\) & \(0.740\) & & \(0.016\) & \(0.639\) & \(0.024\) & \(0.101\) & \(0.27  
Multiple linear regression analysis was conducted to predict settlement based on soil parameters. The results including model summary, ANOVA results, and regression coefficients are presented in Tables 8-10. The regression model showed a high value of 0.846, indicating that 84.6% of the variance in settlement was explained by the predictors. However, the adjusted value of 0.435 indicates possible model overfitting or inclusion of variables with minimal contribution to the settlement prediction. The ANOVA table shows that the model is not statistically significant (\(p\) = 0.299), implying that the combined predictors do not significantly explain the settlement variation in the current dataset. This observation suggests a possible mismatch between the selected parameters and the observed settlement values (Table 9).