This study employs Bayesian network analysis to quantitatively evaluate the risk of incidents in trap boats, utilizing accident compensation approval data spanning from 2018 to 2022. With a dataset comprising 1,635 incidents, the analysis reveals a mortality risk of approximately 0.011 across the entire trap boat. The study significantly identifies variations in incident risks contingent upon fishing area and fishing processes. Specifically, incidents are approximately 1.22 times more likely to occur in coastal compared to offshore, and the risk during fishing processes outweighs that during maintenance operations by a factor of approximately 23.20. Furthermore, a detailed examination of incident types reveals varying incidence rates. Trip/slip incidents, for instance, are approximately 1.36 times more prevalent than bump/hit incidents, 1.58 times more than stuck incidents, and a substantial 5.17 times more than fall incidents. The study concludes by providing inferred mortality risks for 16 distinct scenarios, incorporating fishing areas, processes, and incident types. This foundational data offers a tailored approach to risk mitigation, enabling proactive measures suited to specific circumstances and occurrence types in the trap boat industry.

서 론
자료 및 방법
    분석자료
    분석방법
결과 및 고찰
    산업재해 발생 현황
    베이지안 네트워크를 이용한 위험성 분석
결 론
사 사
References

• 이승현(국립부경대학교 해양생산시스템관리학부 대학원생) | Seung-Hyun LEE (Graduate student, Department of Fisheries Physics, Pukyong National University, Busan 48513, Korea)
• 김수형(국립부경대학교 실습선 교수) | Su-Hyung KIM (Professor, Training Ship, Pukyong National University, Busan 48513, Korea)
• 류경진(국립부경대학교 해양생산시스템관리학부 교수) | Kyung-Jin RYU (Professor, Division of Marine Production System Management, Pukyong National University, Busan 48513, Korea)
• 이유원(국립부경대학교 해양생산시스템관리학부 교수) | Yoo-Won LEE (Professor, Division of Marine Production System Management, Pukyong National University, Busan 48513, Korea) Corresponding author