An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland
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DOI: 10.1016/j.ress.2021.108024
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- Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2024. "A framework for ship abnormal behaviour detection and classification using AIS data," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
- Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Puisa, Romanas & Montewka, Jakub & Krata, Przemyslaw, 2023. "A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Zhang, Mingyang & Zhang, Di & Fu, Shanshan & Kujala, Pentti & Hirdaris, Spyros, 2022. "A predictive analytics method for maritime traffic flow complexity estimation in inland waterways," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
- Gil, Mateusz & Kozioł, Paweł & Wróbel, Krzysztof & Montewka, Jakub, 2022. "Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
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Keywords
Collision-prone locations; The Gulf of Finland; Ship-ship collision frequency; Oil Tankers; Verification Methods; IWRAP Mk2 Software;All these keywords.
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