# Risk Causal Analysis of Traffic-Intensive Waters Based on Infectious Disease Dynamics
## 3 Empirical Case Analysis
### Screening of Key Risk Factors of Ship Navigation
#### 3.1.2 Membership Degree of Key Risk Factors of Navigation  
The initial input value of the risk of ship navigation was obtained by using a cloud model. The Beaufort wind scale of greater than or equal to 6, the visibility, and tide were obtained by quantitative analysis, and the possibility of other risk factors \(P\) can be obtained through Shanghai Maritime Bureau statistics. The degree of influence on the risk factors \(I\) can be obtained through expert survey. In this study, questionnaires were distributed to experts from different sectors including the maritime safety administrations, port authorities, shipping companies, and universities. A total of 1024 questionnaires were sent out, and 982 valid questionnaires were collected. The effective rate was 95.9%. As shown in Table 4, all the experts were professional staff, teachers, and students; 15.79% were shipping company managers, and 16.30% were sea pilots. The experts' education level was high, and all of them have an education background of undergraduate or above. A reliability analysis and validity analysis of the questionnaire results were also conducted in this research. The results show that the Cronbach's coefficient was greater than 0.9, which indicates a high reliability. Besides, the construct validity of the questionnaire was good by factor analysis. Both of the reliability and validity met the needs of psychometric standards. The degree of influence of risk factors \(I\) was calculated. The initial input values of risk factors of ship navigation are shown in Table 5. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Variable** & **Description** & **Frequency** & **Percentage (n = 982): \%** \\ \hline \multirow{7}{*}{Occupation} & Professor & 20 & 2.03 \\  & Research assistant & 45 & 4.58 \\  & Associate professor & 55 & 5.60 \\  & Captain & 90 & 9.16 \\  & Chief officer & 90 & 9.16 \\  & Second officer & 130 & 13.24 \\  & Third officer & 120 & 12.22 \\  & Sea pilot & 160 & 16.30 \\  & Shipping company manager & 155 & 15.79 \\  & Maritime organizations & 117 & 11.92 \\ \hline \multirow{3}{*}{Education level} & Doctor & 60 & 6.11 \\  & Master & 140 & 14.26 \\ \cline{1-1}  & Bachelor & 782 & 79.63 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistics of experts being interviewed. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Risk Source** & \multicolumn{2}{c}{**The Probability of Risk**} \\  & **Occurrence \(P\)** & **Risk Factor Influence Degree \(I\)** \\ \hline Beaufort wind scale is greater than 6 & 0.3753 & 0.101 \\ Visibility & 0.0411 & 0.851 \\ Wave level & 0.2678 & 0.005 \\ Flow state & 0.2232 & 0.102 \\ Tidal & 0.5893 & 0.521 \\ Flow & 0.2946 & 0.057 \\ Channel water depth & 0.0268 & 0.098 \\ Speed & 0.0268 & 0.075 \\ Route complexity & 0.0268 & 0.054 \\ Navigational regulation rationality & 0.3125 & 0.094 \\ VTS coordination degree & 0.0179 & 0.065 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Initial inputs of risk factors. The average degree of influence under different factors in traffic-intensive waters can be obtained by simulation of the above model. For example, the probability of risk occurrence and the degree of risk factor (x\({}_{p}\), x\({}_{i}\)) = (0.3753, 0.101) of the number of days that the Beaufort wind scale was greater than 6 in a month are imported to the cloud model. After substituting into the cloud rule generator, the cloud droplets can be generated by using MATLAB software. Finally, the risk cloud parameters with respect to the risk factor when the Beaufort wind scale is greater than 6 days are obtained. The value of \(E_{x}\), \(E_{n}\), and \(H_{e}\) is 0.0384, 0.0596, and 0.0339, respectively (see Figure 4). It can be seen from Table 6 that the values of \(H_{e}\) of the ship traffic flow density, tide, onboard officer skill, onboard officer duties, Beaufort wind scale of 6 or greater, and poor visibility are high. It is noted that the higher the \(H_{e}\), the greater the degree of risk.