## 4 Case Study
### Discussion  
From the results of the simulation based on the micro- and macro-level case studies, the comprehensive risk was inferred using a fuzzy set theory-based obstacle risk assessment system that simultaneously considers both the collision and pollution risks. This system was designed to infer the comprehensive risk by evaluating both the collision and pollution risks in an integrated manner. Through this approach, the system aims to support decision-making for the prompt removal of navigational obstacles.  
In the micro-level case study, the collision risk index calculated from the collision risk assessment model and the pollution risk index calculated from the pollution risk assessment were input into the developed model. The comprehensive risk was inferred using fuzzy rules by applying 24 AND operations. Because of the nature of the AND operation, the  
Figure 15: Fuzzy set theory-based risk assessment in micro-level case study.  
final result is considered true only when all conditions are true, allowing for more accurate results by returning an outcome only when all conditions are satisfied [22]. The models calculated the collision and pollution risks as 6.37% and 16.00%, respectively. When these risk factors were analyzed using the fuzzy rule with AND operations, a low comprehensive risk state of 48.74% was inferred. This indicates that the system can provide reliable risk assessment by comprehensively considering both the collision and pollution risks.  
In the macro-level case study, the comprehensive risk was inferred by calculating the pollution risk index for each location using the data on the current status of sunken ships from the Korea Maritime Environment Corporation (Seoul, Republic of Korea) and by adding an arbitrary index according to the collision risk level. In this process, it was confirmed that the comprehensive risk tended to increase as the collision risk level increased. This indicates that collision risk is an important variable for the evaluation of the comprehensive risk. Furthermore, the results suggest that higher levels of the comprehensive risk may require stricter operational measures, such as prioritizing the removal of obstacles in high-risk areas or deploying additional resources for monitoring and response. Additionally, future adaptations of this model could integrate additional factors, such as the economic impact of assessed risks, to enhance its practical applicability. This extension would facilitate the evaluation of how risk levels influence costs and resource allocation, making the model more comprehensive for real-world decision-making.  
The reliability of the system was verified by comprehensively evaluating the collision risk index and pollution risk index in various situations and inferring the comprehensive risk index and level. In particular, the developed system not only overcomes the limitations of previous research, which failed to simultaneously consider the collision and pollution risks but also demonstrates its potential as an effective decision-making tool for the prompt removal of navigational obstacles.  
Figure 16: Distribution of comprehensive risk by location for (**a**) very low, (**b**) low, (**c**) medium, (**d**) high, and (**e**) very high collision risk index.