Use of fuzzy fault tree analysis and noisy-OR gate bayesian network for navigational risk assessment in Qingzhou Port

• Autorzy: Zhao C. , Wu B. , Yip T. L. , Lv J.

Identyfikatory

DOI

10.12716/1001.15.04.07

• Języki publikacji: EN

Abstrakty

EN

Collisions and groundings account for more than 80% among all types of maritime accidents, and risk assessment is an essential step in the formal safety assessment. This paper proposes a method based on fuzzy fault tree analysis and Noisy-OR gate Bayesian network for navigational risk assessment. First, a fault tree model was established with historical data, and the probability of basic events is calculated using fuzzy sets. Then, the Noisy-OR gate is utilized to determine the conditional probability of related nodes and obtain the probability distribution of the consequences in the Bayesian network. Finally, this proposed method is applied to Qinzhou Port. From sensitivity analysis, several predominant influencing factors are identified, including navigational area, ship type and time of the day. The results indicate that the consequence is sensitive to the position where the accidents occurred. Consequently, this paper provides a practical and reasonable method for risk assessment for navigational accidents.

Słowa kluczowe

EN

risk assessment; Bayesian Network Model; navigational risk; navigational risk assessment; Port of Qingzhou; fuzzy fault tree; noisy-OR gate; navigational accidents

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2021
• Tom: Vol. 15 No. 4
• Strony: 765--771
• Opis fizyczny: Bibliogr. 18 poz., rys., tab.

Twórcy

autor

Zhao C.

• Intelligent Transportation System Research Center (ITSC), Wuhan, China
• National Engineering Research Center for Water Transport Safety, Wuhan, China
• Wuhan University of Technology, Wuhan, China

autor

Wu B.

• Intelligent Transportation System Research Center (ITSC), Wuhan, China
• National Engineering Research Center for Water Transport Safety, Wuhan, China
• Wuhan University of Technology, Wuhan, China

autor

Yip T. L.

• Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

autor

Lv J.

• Shenzhen CIMC Intelligent Technology Co. Ltd., Shenzhen, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).