## 6 Discussion
### Comparison of Different Evaluation Methods  
The Classic SPA [8], FCE [12], GCM [13], BPNN [14], and SVM [15] were selected to calculate the risk level of the case to evaluate the advantages of the improved SPA. The Classic SPA, FCE, and GCM calculate the index weights based on the PP. A sigmoid activation function is used in the BPNN, and the minimum convergence error is \(10^{-5}\). For the SVM model, 10 groups of parameters are randomly selected, and the average of the 10 calculation results is used as the risk analysis result.  
The FCE evaluation result of the case is [0.000, 0.172, 0.347, 0.343, 0.228]; therefore, the construction risk level is IV. Although the two evaluation models provide different levels of construction risk, the degree of membership of III and IV is relatively close. The weights of some indicators substantially affect the evaluation results, and the weights of some key indicators are large. Thus, they skew the result. The SPA method avoids this problem, accurately reflects the differences between the evaluation units, and provides a more accurate assessment of the uncertainty and risk of the project.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Index**} & \multicolumn{2}{c}{**PP**} & \multicolumn{2}{c}{**AHP**} & \multicolumn{2}{c}{**Entropy Weight**} \\ \cline{2-7}  & **Weight** & **Ranking** & **Weight** & **Ranking** & **Weight** & **Ranking** \\ \hline \(R_{11}\) & 0.0379 & 16 & 0.0150 & 23 & 0.0206 & 21 \\ \(R_{12}\) & 0.0238 & 22 & 0.0258 & 22 & 0.0361 & 13 \\ \(R_{13}\) & 0.0380 & 15 & 0.0408 & 15 & 0.0293 & 16 \\ \(R_{14}\) & 0.0448 & 11 & 0.0494 & 8 & 0.0447 & 11 \\ \(R_{15}\) & 0.0552 & 4 & 0.0665 & 2 & 0.0103 & 23 \\ \(R_{21}\) & 0.0641 & 1 & 0.0668 & 1 & 0.0290 & 17 \\ \(R_{22}\) & 0.0292 & 20 & 0.0297 & 20 & 0.0987 & 1 \\ \(R_{23}\) & 0.0624 & 2 & 0.0445 & 10 & 0.0547 & 8 \\ \(R_{24}\) & 0.0312 & 19 & 0.0414 & 12 & 0.0643 & 3 \\ \(R_{31}\) & 0.0435 & 13 & 0.0411 & 13 & 0.0286 & 18 \\ \(R_{32}\) & 0.0478 & 8 & 0.0587 & 4 & 0.0689 & 2 \\ \(R_{33}\) & 0.0511 & 7 & 0.0446 & 9 & 0.0546 & 9 \\ \(R_{34}\) & 0.0375 & 17 & 0.0528 & 5 & 0.0338 & 15 \\ \(R_{35}\) & 0.0445 & 12 & 0.0376 & 16 & 0.0182 & 22 \\ \(R_{41}\) & 0.0598 & 3 & 0.0632 & 3 & 0.0591 & 6 \\ \(R_{42}\) & 0.0433 & 14 & 0.0316 & 18 & 0.0231 & 19 \\ \(R_{43}\) & 0.0551 & 5 & 0.0368 & 17 & 0.0563 & 7 \\ \(R_{44}\) & 0.0539 & 6 & 0.0421 & 11 & 0.0416 & 12 \\ \(R_{51}\) & 0.0192 & 23 & 0.0292 & 21 & 0.0216 & 20 \\ \(R_{52}\) & 0.0370 & 18 & 0.0410 & 14 & 0.0461 & 10 \\ \(R_{53}\) & 0.0265 & 21 & 0.0302 & 19 & 0.0617 & 5 \\ \(R_{54}\) & 0.0468 & 10 & 0.0496 & 7 & 0.0345 & 14 \\ \(R_{55}\) & 0.0476 & 9 & 0.0498 & 6 & 0.0641 & 4 \\ \(R_{1}\) & 0.1997 & 3 & 0.1975 & 2 & 0.1411 & 5 \\ \(R_{2}\) & 0.1869 & 4 & 0.1824 & 4 & 0.2467 & 1 \\ \(R_{3}\) & 0.2244 & 1 & 0.2347 & 1 & 0.2042 & 3 \\ \(R_{4}\) & 0.2121 & 2 & 0.2079 & 3 & 0.1801 & 4 \\ \(R_{5}\) & 0.1771 & 5 & 0.1775 & 5 & 0.2279 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Results of different weight calculation methods.  
The calculation results of the gray correlation degree of the risk levels obtained from the GCM are listed in Table 8. The gray correlation degree of the case is 0.4956, and the risk level is III. The evaluation results are consistent with the SPA method. The GCM prevents ambiguity of the indices. However, the method is too subjective for this project because the optimal values of the secondary indices are predetermined, unlike in the SPA method.  
The results of the BPNN and SVM are listed in Table 9. The results differ substantially. The reason may be that the sample size is too small to train the BPNN and SVM.