## 4 Analysis and Results
### Method Contrast  
To ensure the accuracy of the model, the same five sets of expert scoring data were selected for fuzzy comprehensive evaluation analysis in the study [35]. The results were compared with the findings of the normal cloud model for validation. The sets of indicator weights \(A\), \(B_{i}(i=1,2,\ldots,5)\), constructed based on ANP, shown as follows:  
\[A=[0.038\ 0.529\ 0.251\ 0.122\ 0.075]\] \[B_{1}=[0.7802\ 0.0078\ 0.2121]\] \[B_{2}=[0.1042\ 0.3629\ 0.3990\ 0.1339]\] \[B_{3}=[0.1114\ 0.1808\ 0.4008\ 0.3070]\] \[B_{4}=[0.1347\ 0.7188\ 0.1466]\] \[B_{5}=[0.6527\ 0.1218\ 0.2256]\]  
The evaluation matrix \(C_{i}\) (\(i=1,2,\ldots,5\)) was constructed based on the expert scoring results to second-level elements of the LNG tank leakage accident:  
\[C_{1}=\begin{bmatrix}0&1&3&1&0\\ 0&0&0&3&0\\ 0&0&0&3&0\\ 0&0&0&3&0\\ 0&0&0&3&0\\ 0&0&0&3&0\\ 0&0&0&3&0\\ \end{bmatrix};C_{2}=\begin{bmatrix}0&0&0&4&1\\ 0&0&0&3&0\\ 0&0&0&3&0\\ 0&0&3&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ \end{bmatrix};C_{5}=\begin{bmatrix}0&0&2&3&0\\ 0&1&3&0&0\\ 0&0&3&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ \end{bmatrix};C_{5}=\begin{bmatrix}0&0&2&3&0\\ 0&1&3&0&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ \end{bmatrix};C_{5}=\begin{bmatrix}0&0&2&3&0\\ 0&1&3&0&0\\ 0&0&3&0&3&0\\ 0&0&3&0&3&0\\ \end{bmatrix};C_{5}=\begin{bmatrix}0&1&3&0&0\\ 0&1&3&0&0\\ 0&0&3&0&3&0\\  
According to the fuzzy affiliation matrix \(S\) calculated in Equation (10), the affiliation of LNG leakage accident in level IV is the largest at 0.5095. Based on the principle of maximum affiliation, the preliminary judgment of the accident risk level is \"High risk\".  
In order to calculate the fuzzy comprehensive evaluation score of the accident, based on the risk levels classified above, the risk level matrix was assumed as \(L=[Ex_{1},Ex_{2},Ex_{3},Ex_{4},Ex_{5}]^{T}\). The safety risk of the LNG storage tank leakage accident was calculated with Equation (11) in the paper.  
\[R=S\times L \tag{11}\]  
The calculation yields that \(R=[S_{1}\ S_{2}\ S_{3}\ S_{4}\ S_{5}]\times[Ex_{1}\ Ex_{2}\ Ex_{3}\ Ex_{4}\ Ex_{5}]^{T}=0.7586 \in[0.5,0.8)\).  
The same method was used for all the first-level indicators, and the evaluation results of the two methods are shown in Table 10.  
The result of the fuzzy comprehensive evaluation of \"High-risk substances\" was 0.5043 \(>\) 0.5. However, according to the \"maximum membership principle\", the affiliation of the B5 indicator to level III is known to be 0.5390, and the affiliation to level IV is 0.4367, and 0.5390 \(>\) 0.4367. The risk level of the index belongs to the level III.  
In conclusion, the evaluation results of the fuzzy comprehensive evaluation are the same as those of the normal cloud model. The results of both models were judged to be realistic and in general agreement with the results of the safety assessment report for the tank. It can be proved that the ANP-normal cloud assessment model has high accuracy.  
From the perspective of the \"Five-high\" risks, \"High-risk equipment\" has the highest level of risk and impact and has the highest weighting. As the largest part of the LNG storage area, the safety of the equipment is particularly important. The risk level of secondary element C23 reaches level V, which requires the enterprise to immediately stop work for rectification and inspection to reduce the risk.  
From an intrinsic safety perspective, the enterprise should focus on the regular review and maintenance of the safety performance of the equipment itself. In addition, the enterprise should focus on the management and assessment of operators and strictly eliminate the \"three violations\", optimizing the allocation of resources and improving the safety and security of the entire \"man-machine-environment\" system to achieve intrinsic safety.