## 2 Evaluation Method
### Comprehensive Evaluation of Two-Dimensional Cloud Model
#### 2.5.2 Construction of Two-Dimensional Cloud Model  
(1) Risk Cloud \(C^{n}\)  
The risk cloud is a cloud model generated by evaluating the original data through a reverse cloud generator, and it is a comprehensive representation of the probability of risk occurrence and the severity of consequences. This paper invites experts to score and assign risk indicators based on the two criteria of risk occurrence probability and consequence severity. The score range is [0, 100] and the score accuracy is 1, so as to obtain the risk probability cloud and risk consequence cloud. The numerical eigenvalues of the risk probability cloud and the risk consequence cloud can be obtained through Formula (27), the reverse cloud generator's calculation formula. \[\left\{ \begin{array}{l}Ex^{n}=\frac{1}{n}\sum\limits_{i=1}^{n}x_{i}\\ En^{n}=\frac{1}{n}\sqrt{\frac{2}{\sum\limits_{l=1}^{n}\left|x_{i}-Ex^{n}\right| }}\\ He^{n}=\sqrt{S^{2}-En^{n2}}\\ S^{2}=\frac{1}{n-1}\sum\limits_{i=1}^{n}\left(x_{i}-Ex^{n}\right)^{2}\end{array} \right. \tag{27}\]In the formula, \(x_{i}\) represents the scoring data of the \(i\)-th expert; \(S^{2}\) is the variance of the data; \(Ex^{n}\) is the expected value of the risk cloud; \(En^{n}\) is the entropy value of the risk cloud; and \(He^{n}\) is the super-entropy value of the risk cloud. (2) Standard Cloud \(C^{m}\)  
The standard cloud is a cloud model generated by evaluation standards. Divide the risk probability level and consequence level into 5 levels and quantify them; the quantified level range is \(\left[\lambda_{\text{min}}^{i},\lambda_{\text{max}}^{i}\right],(i=1,2,3,4,5)\). \(\lambda_{\text{min}}^{i}\) and \(\lambda_{\text{max}}^{i}\) are the quantified upper and lower limits of the \(i\)-th risk level, respectively. Then use the quantified minimum value \(\lambda_{\text{min}}^{i}\) and maximum value \(\lambda_{\text{max}}^{i}\) of the grade interval to establish five one-dimensional standard clouds based on probability and consequence criteria and combine the two to generate five two-dimensional standard clouds; the digital characteristic values of standard clouds in each grade interval are determined by Formula (28). The risk grade scores and digital characteristics of standard clouds are shown in Table 3[31]. \[\left\{ \begin{array}{l}Ex^{m}=\left(\lambda_{\text{min}}^{i}+\lambda_{ \text{max}}^{i}\right)/2\\ En^{m}=\left(\lambda_{\text{max}}^{i}-\lambda_{\text{min}}^{i}\right)/2.35 \end{array} \right. \tag{28}\]  
In the formula, \(Ex^{m}(En^{m})He^{m}\) are the expectation of the standard cloud, the entropy, and the super-entropy, \(k\) is a constant, and the value is adjusted by the degree of conceptual fuzziness, which is taken as 0.1 in this paper. According to the standard cloud digital characteristics in Table 3, taking the probability of risk occurrence and the severity of risk consequences as benchmarks, we used MATLAB programming to draw a two-dimensional standard cloud map, as shown in Figure 5.  
Figure 5: Two-dimensional standard cloud map. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Risk Level** & **Possibility** & **Severity** & **Quantitative Range of** & **Standard Cloud** \\
**Description** & **Description** & **Description** & **Risk Level** & **Digital Characteristics** \\ \hline I & extremely impossible & slight & \([0,20)\) & \((10,8.49,0.85)\) \\ II & impossible & larger & \([20,40)\) & \((30,8.49,0.85)\) \\ III & occasionally & serious & \([40,60)\) & \((50,8.49,0.85)\) \\ IV & possible & very serious & \([60,80)\) & \((70,8.49,0.85)\) \\ V & extremely possible & disastrous & \([80,100]\) & \((90,8.49,0.85)\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Standard cloud digital characteristics.