## 5 Results and Discussions  
Based on the work in Table 10, the synthetic attribute measure is obtained using Equation (22). The variable weights of the evaluation indices are from Table 9. Additionally, the risk grade is determined using Equation (24). \(\lambda\) is 0.65 in this paper. The evaluation grade results and comparison with other methods [39] are shown in Table 11.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Section**} & \multirow{2}{*}{**I**} & \multirow{2}{*}{**II**} & \multirow{2}{*}{**III**} & \multirow{2}{*}{**IV**} & \multirow{2}{*}{**Introduced**} & \multicolumn{2}{c}{**Traditional**} & \multicolumn{2}{c}{**Analytic**} & \multirow{2}{*}{**Field**} \\  & & & & **Attributes** & & & **Attributes** & & **Hierarchy** & **Recall** \\ \hline
1 & 0.007 & 0.489 & 0.421 & 0.083 & II & II & II & II \\
2 & 0.008 & 0.503 & 0.470 & 0.019 & II & III & III & II \\
3 & 0.164 & 0.674 & 0.162 & 0.000 & II & II & II & II \\
4 & 0.413 & 0.554 & 0.033 & 0.000 & I & I & II & I \\
5 & 0.080 & 0.458 & 0.357 & 0.105 & II & II & II & II \\
6 & 0.177 & 0.372 & 0.270 & 0.181 & II & II & III & II \\ \hline \hline \end{tabular}
\end{table}
Table 11: Risk assessment results of water inrush.  
In Table 11, the final levels of the 1, 2, 3, 4, 5, and 6 sections are II, II, II, I, II, and II. Compared to the two methods mentioned above, the proposed method had agreements of 50% and 83%, respectively. It can be clearly seen that the improved method has a 17% improvement in the prediction accuracy over the traditional method. The risk levels for Section 1, Section 3, Section 4, Section 5, and Section 6 are consistent with the traditional method. The risk levels for Section 1, Section 3, and Section 5 are consistent with the AHP method. Importantly, the risk levels of Section 2, Section 4, and Section 6 are not consistent with AHP method. This is because the AHP method is more conservative than the other method. Additionally, the calculation of the eigenvalues and eigenvectors in the AHP method is complex. In general, there is a high degree of consistency in the results of the different methods. Among them, the method proposed in this paper is more accurate and effective.  
The practical situations of the Qiyueshan Tunnel are shown in Figure 14. The water inrush appeared on the left wall in Section 1 (Figure 14a). The tunnel flooding situation is shown in Figure 14b. Therefore, the evaluation results of this method are consistent with the field observation results.  
The average risk level of the tunnel is II. The maximum water inflow of this tunnel is 87,000 m\({}^{3}\)/d. The death toll was 11 and the direct economic losses amounted to 53.21 million. Additionally, this is a high-risk project and a response contingency plan, so early warning drills should be developed prior to construction [40].  
The application of the improved non-linear attribute variable weight evaluation model was successful, but it has some limitations. The weight obtained using MFIM and the C-OWA operator was determined by several experts, and the correctness of the results depends on the experience as well as the knowledge of different experts, while the method is subjective. At the same time, the evaluation index system has more qualitative indicators and less quantitative indicators, which have some influence on the results. In future research, the evaluation indicators should be more quantitative to cause the evaluation results to be more objective. In addition, through theoretical as well as numerical and experimental analysis, developing an understanding of the interaction of risk elements, as well as the impact on the water inrush, is important.