On the causation correlation of maritime accidents based on data mining techniques
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DOI: 10.1177/1748006X221131717
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References listed on IDEAS
- Çakır, Erkan & Fışkın, Remzi & Sevgili, Coşkan, 2021. "Investigation of tugboat accidents severity: An application of association rule mining algorithms," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
- Zhou, Ying & Li, Chenshuang & Ding, Lieyun & Sekula, Przemyslaw & Love, Peter E.D. & Zhou, Cheng, 2019. "Combining association rules mining with complex networks to monitor coupled risks," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 194-208.
- Weiliang Qiao & Yu Liu & Xiaoxue Ma & Yang Liu, 2020. "Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 957-980, May.
- Yang, Zhe & Baraldi, Piero & Zio, Enrico, 2020. "A novel method for maintenance record clustering and its application to a case study of maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
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Keywords
Maritime accidents; risk analysis; text mining; association rule; FP-Growth algorithm;All these keywords.
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