Journal is indexed in following databases:
- SCOPUS
- Web of Science Core Collection - Journal Citation Reports
- EBSCOhost
- Directory of Open Access Journals
- TRID Database - Transportation Research Board
- Index Copernicus Journals Master List
- BazTech
- Google Scholar
2023 Journal Impact Factor - 0.7
2023 CiteScore - 1.4
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
Use of Fuzzy Fault Tree Analysis and Noisy-OR Gate Bayesian Network for Navigational Risk Assessment in Qingzhou Port
Times cited (SCOPUS): 3
ABSTRACT: 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.
KEYWORDS: Risk Assessment, Navigational Risk, Bayesian Network Model, Navigational Risk Assessment, Port of Qingzhou, Fuzzy Fault Tree, Noisy-OR Gate, Navigational Accidents
REFERENCES
Arici, S.S., Akyuz, E., Arslan, O.: Application of fuzzy bow-tie risk analysis to maritime transportation: The case of ship collision during the STS operation. Ocean Engineering. 217, 107960 (2020). - doi:10.1016/j.oceaneng.2020.107960
Chen, S.-J., Hwang, C.-L.: Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin Heidelberg (1992). - doi:10.1007/978-3-642-46768-4
Erol, S., Demir, M., Çetişli, B., Eyüboğlu, E.: Analysis of Ship Accidents in the Istanbul Strait Using Neuro-Fuzzy and Genetically Optimised Fuzzy Classifiers. Journal of Navigation. 71, 2, 419–436 (2018). - doi:10.1017/S0373463317000601
Feng, X., Jiang, J., Wang, W.: Gas pipeline failure evaluation method based on a Noisy-OR gate bayesian network. Journal of Loss Prevention in the Process Industries. 66, 104175 (2020). - doi:10.1016/j.jlp.2020.104175
Oniśko, A., Druzdzel, M.J., Wasyluk, H.: Learning Bayesian network parameters from small data sets: application of Noisy-OR gates. International Journal of Approximate Reasoning. 27, 2, 165–182 (2001). - doi:10.1016/S0888-613X(01)00039-1
Ozturk, U., Cicek, K.: Individual collision risk assessment in ship navigation: A systematic literature review. Ocean Engineering. 180, 130–143 (2019). - doi:10.1016/j.oceaneng.2019.03.042
Peng, X., Yao, D., Liang, G., Yu, J., He, S.: Overall reliability analysis on oil/gas pipeline under typical third-party actions based on fragility theory. Journal of Natural Gas Science and Engineering. 34, 993–1003 (2016). - doi:10.1016/j.jngse.2016.07.060
Rajakarunakaran, S., Maniram Kumar., A., Arumuga Prabhu, V.: Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station. Journal of Loss Prevention in the Process Industries. 33, 109–123 (2015). - doi:10.1016/j.jlp.2014.11.016
Shabarchin, O., Tesfamariam, S.: Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model. Journal of Loss Prevention in the Process Industries. 40, 479–495 (2016). - doi:10.1016/j.jlp.2016.02.001
Vinod, G., Kushwaha, H.S., Verma, A.K., Srividya, A.: Importance measures in ranking piping components for risk informed in-service inspection. Reliability Engineering & System Safety. 80, 2, 107–113 (2003). - doi:10.1016/S0951-8320(02)00270-3
Wang, D., Zhang, P., Chen, L.: Fuzzy fault tree analysis for fire and explosion of crude oil tanks. Journal of Loss Prevention in the Process Industries. 26, 6, 1390–1398 (2013). - doi:10.1016/j.jlp.2013.08.022
Wang, L.X.: A course on fuzzy systems and control. (1996).
Wang, Y., Zio, E., Wei, X., Zhang, D., Wu, B.: A resilience perspective on water transport systems: The case of Eastern Star. International Journal of Disaster Risk Reduction. 33, 343–354 (2019). - doi:10.1016/j.ijdrr.2018.10.019
Wróbel, K., Montewka, J., Kujala, P.: Towards the assessment of potential impact of unmanned vessels on maritime transportation safety. Reliability Engineering & System Safety. 165, 155–169 (2017). - doi:10.1016/j.ress.2017.03.029
Wu, B., Yip, T.L., Yan, X., Mao, Z.: A Mutual Information-Based Bayesian Network Model for Consequence Estimation of Navigational Accidents in the Yangtze River. Journal of Navigation. 73, 3, 559–580 (2020). - doi:10.1017/S037346331900081X
Zadeh, L.A.: Fuzzy sets. Information and Control. 8, 3, 338–353 (1965). - doi:10.1016/S0019-9958(65)90241-X
Zhang, D., Yan, X., Zhang, J., Yang, Z., Wang, J.: Use of fuzzy rule-based evidential reasoning approach in the navigational risk assessment of inland waterway transportation systems. Safety Science. 82, 352–360 (2016). - doi:10.1016/j.ssci.2015.10.004
Zhang, J., Teixeira, Â.P., Guedes Soares, C., Yan, X., Liu, K.: Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks. Risk Anal. 36, 6, 1171–1187 (2016). - doi:10.1111/risa.12519
Citation note:
Zhao C.C., Wu B., Yip T.L., Lv J.: Use of Fuzzy Fault Tree Analysis and Noisy-OR Gate Bayesian Network for Navigational Risk Assessment in Qingzhou Port. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 15, No. 4, doi:10.12716/1001.15.04.07, pp. 765-771, 2021
Other publications of authors:
File downloaded 274 times
