## 3 Method
### Fuzzy-DEMATEL  
Fuzzy mathematics is based on the fuzzy set theory, which is applicable to the analysis of the fuzzy degree of correlation between elements. It is a method of processing fuzzy information simulating the human brain. By introducing the fuzzy set theory and the subjective judgment of experts in triangular fuzzy number, it can eliminate the subjectivity of experts' scoring [47].  
Fuzzy-DEMATEL method can not only retain the advantages of traditional DEMATEL method in factor recognition [48], but also replaces the original accurate value with triangular. Fuzzy number reflect the real situation of the problem more comprehensively. It improves the credibility of the analysis results and provides a reliable reference for managers to make decisions [49]:  
1. For the problem under study, established a system of influencing factors set to F1, F2,..., Fn.
2. According to the expert scoring method to determine the influence relationship between the methods, and the matrix form is used to express. Experts were invited to evaluate the relationship between methods using language operators \"no influence (N)\", \"very weak influence (VL)\", \"weak influence (L)\", \"strong influence (H)\", and \"very strong influence (VH)\". The original expert evaluation is converted into triangular fuzzy number by means of semantic table, which represents  
Figure 1: Research design.  
the influence of i method on j method according to the KTH expert, as shown in Table 3. Conversion from language variables to triangular fuzzy Numbers: \[W_{ij}^{k}=(a_{1 ij}^{k},a_{2 ij}^{k},a_{3 ij}^{k})=(\max\biggl{\{}\frac{i-1}{n},0 \biggr{\}},\frac{i}{n},\min\biggl{(}\frac{i-1}{n},1\biggr{\}})i\in\{0,1,\cdots n\}\] (1) where k is the kth questionnaire of expert, while i and j are the row and column number of the risk prevention method matrix, respectively.
* The method of converting the Fuzzy data into crips scores (CFCS) is used to defuzzify the initial values of the expert scores, as the nth order directly affects the matrix Z, and the direct influence matrix reflects the direct effect between the factors, including the following four steps:
* Normalize triangular fuzzy numbers: \[\begin{array}{l}xa_{1 ij}^{k}=(a_{1 ij}^{k}-\min a_{1 ij}^{k})/\Delta_{\min}^{ \max}\\ x_{2 ji}^{k}=(a_{2 ij}^{k}-\min a_{1 ij}^{k})/\Delta_{\min}^{\max}\\ x_{3 ij}^{k}=(a_{3 ij}^{k}-\min a_{1 ij}^{k})/\Delta_{\min}^{\max}\\ \end{array}\] (2) Among them, \(\Delta_{\min}^{\max}=\max a_{3 ij}^{k}-\min a_{1 ij}^{k}\); In turn, we can calculate \(xa_{1 ij}^{k}\), \(xa_{2 ij}^{k}\), \(xa_{3 ij}^{k}\).
* Standardize left and right values: \[\begin{array}{l}xls_{ij}^{k}=xa_{2 ij}^{k}/(1+xa_{2 ij}^{k}-xa_{1 ij}^{k})\\ xrs_{ij}^{k}=xa_{3 ij}^{k}/(1+xa_{3 ij}^{k}-xa_{2 ij}^{k})\\ \end{array}\] (3)
* Calculate the clear value after defuzzification: \[\begin{array}{l}x_{ij}^{k}=[xls_{ij}^{k}(1-xls_{ij}^{k})+xrs_{ij}^{k}xrs_{ ij}^{k}]/[1-xls_{ij}^{k}+xrs_{ij}^{k}]\\ z_{ij}^{k}=\min a_{1 ij}^{k}+x_{ij}^{k}\times\Delta_{\min}^{\max}\\ \end{array}\] (4)
* Calculate the average clear value:  
Sum of the degree of influence and the influence degree on other factors is called centrality \(\text{m}_{i}\), indicating the position of the method in the system and the size of the effect. The difference between the degree of influence and the degree to be influenced is called the degree of cause \(\text{n}_{i}\), which reflects the causal relationship between the influencing methods. If the causality is greater than 0, the factor has a great effect on other factors and is called the factor of cause. If the causality is less than 0, the factor is greatly affected by other factors and is called the factor of result. The formulas are as follows:  
\[\begin{array}{l}m_{i}=D_{i}+R_{i}(i=1,2,\cdots,n)\\ n_{i}=D_{i}+R_{i}(i=1,2,\cdots,n)\end{array} \tag{8}\]  
* Based on the above analysis of the importance of each method and the interaction between the methods, for the actual system to put forward policy recommendations.