## 5 Discussion  
### Comparative Analysis  
To verify the effectiveness of the proposed risk assessment model for track maintenance operations, both linear and nonlinear FCE were used to assess the risks of the operations \(A_{1}-A_{5}\). A comparative analysis of the risk assessment results was then conducted. In the linear FCE method, all influence coefficients for the risk indices were uniformly set to 1. From the resulting risk levels, as presented in Table 10, the risk levels of operations \(A_{1}-A_{4}\) are \"General risk (III)\", and operation \(A_{5}\) is \"Minor risk (IV)\". However, when \begin{table}
\begin{tabular}{c c c c c} \hline  & \multicolumn{2}{c}{**Nonlinear FCE**} & \multicolumn{2}{c}{**Linear FCE**} \\ \cline{2-5}
**Operation No.** & **Risk Evaluation Result** & **Risk Level** & **Risk Evaluation Result** & **Risk Level** \\  & **Vector** & & **Vector** & **Risk Level** \\ \hline \(A_{1}\) & (0.252, **0.257**, 0.248, 0.242) & Relatively large risk (II) & (0.213, 0.32, **0.321**, 0.146) & General risk (III) \\ \(A_{2}\) & (0.244, **0.263**, 0.254, 0.239) & Relatively large risk (II) & (0.103, 0.386, **0.433**, 0.078) & General risk (III) \\ \(A_{3}\) & (0.245, 0.256, **0.263**, 0.237) & General risk (III) & (0.124, 0.338, **0.538**, 0) & General risk (III) \\ \(A_{4}\) & (0.237, 0.240, **0.277**, 0.245) & General risk (III) & (0, 0.06, **0.707**, 0.233) & General risk (III) \\ \(A_{5}\) & (0.236, 0.236, **0.264**, 0.263) & General risk (III) & (0, 0, 0.484, **0.515**) & Minor risk (IV) \\ \hline \end{tabular}
\end{table} 
Table 10: Comparison of the risk evaluation results of nonlinear and linear FCE. the nonlinear FCE method was applied for risk assessment, the results for \(A_{1}\), \(A_{2}\), and \(A_{5}\) showed significant differences. This variation is attributed to the nonlinear FCE method's consideration of the dominant influence of certain risk factors in determining overall risk. As a result, the risk levels of operations \(A_{1}\), \(A_{2}\), and \(A_{5}\) were higher than those assessed using the linear FCE method. Specifically, operations \(A_{1}\) and \(A_{2}\) were classified as \"Relatively large risk (II)\", while operation \(A_{5}\) is \"General Risk (III)\". Operations \(A_{1}\) and \(A_{2}\) involve multi-department collaboration, complex pre-operation preparations, high technical difficulty, and intricate work procedures. However, in practice, challenges such as high proportion of outsourced personnel, insufficient safety education, and inadequate protective measures are commonly observed. The nonlinear FCE method accounts for the substantial influence of key risk indices, including the proportion of newly hired or outsourced personnel (\(B_{14}\)), safety education and training (\(B_{41}\)), and safety protection measures (\(B_{42}\)). To enhance the accuracy of risk assessment, we revised the model by assigning higher prominent influence coefficients to these key indices. For example, the status values of risk factors \(B_{41}-B_{44}\) for operation \(A_{1}\) are at levels I, II, IV, and IV, respectively. When using linear FCE, the final status value for \(B_{4}\) is Level IV, which significantly underestimates the risks stemming from inadequate safety education and protective measures. By contrast, by applying nonlinear FCE and incorporating the dominant effects of risk factors \(B_{41}\) and \(B_{42}\), the status value of \(B_{4}\) is adjusted to Level I. This adjustment allows the model to more accurately reflect the risk level of the operation. For operation \(A_{5}\), although the overall status of most risk factors is favorable, there remains room for improvement in the proportion of newly hired or outsourced personnel (\(B_{14}\)) and in safety education and training (\(B_{41}\)). Owing to the current situation, characterized by a high proportion of temporary workers and insufficient safety education prior to the operation, the nonlinear FCE method enhances the influence of these specific indices by introducing prominent influence coefficients.