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베이지안 네트워크를 이용한 항로표지사고 주요 요인 분석

Analysis of Main Factors in aids to Navigation Accidents using a Bayesian Network

  • Sangwon Park (Korea Maritime Institute) ;
  • Youngsoo Park (Division of Navigation Convergence Studies, Korea Maritime and Ocean University) ;
  • Beom-Sik Moon (Korea Maritime and Ocean University)
  • 투고 : 2023.11.06
  • 심사 : 2023.11.29
  • 발행 : 2023.12.31

초록

항로표지는 선박의 위치·방향 및 장애물의 위치 등을 알려주는 항행보조시설로써 중단없는 서비스가 중요하다. 본 연구는 서비스의 중단을 야기하는 항로표지 사고를 분석하고 사고와 관련된 주요 요인을 도출하는 것이 목적이다. 이를 위해 2000년부터 2022년까지 발생한 항로표지 사고자료를 활용했다. 항로표지 사고의 변수를 사고유형, 원인, 지방청, 계절, 항로표지 유형으로 구분했으며, 상관관계 분석을 통해 네트워크를 도출했다. 항로표지 사고 기반으로 도출한 베이지안 네트워크에 사전확률을 부여하고, 항로표지 사고 유형별로 발생 확률을 높이는 요소들을 도출했다. 도출된 결과는 신고되지 않은 항로표지 사고의 원인을 추론할 수 있으며, 항로표지 사고 예방을 위한 기초 자료로도 사용할 수 있다.

Aids to navigation, which provide information about a ship's position, direction, and the location of obstacles, are crucial for uninterrupted maritime services. This study aimed to analyze accidents involving aids to navigation that resulted in service disruptions and identify the key factors associated with these accidents. Aids to navigation accident data from 2000 to 2022 were utilized to achieve this. We categorized accidents by accident type, cause, region, season, and type of navigation aid and established a network through correlation analysis. Bayesian networks based on aids to navigation accidents were assigned prior probabilities, and the factors that increased the probability of accidents for different types of aids to navigation were identified. The findings can be used to infer the causes of unreported aids to navigation accidents and serve as foundational data for the prevention of such accidents.

키워드

과제정보

이 논문은 2021년 해양수산부 재원으로 해양수산과학기술진흥원의 지원을 받아 수행된 연구임(해양 디지털 항로표지정보협력시스템 개발(3/5) (20210650).

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