Akademik Veri Yönetim Sistemi
SHIPS AND OFFSHORE STRUCTURES, 2025 (SCI-Expanded, Scopus)
This research aims to discover the implicit and meaningful relations between the factors that cause accidents by examining the accidents involving offshore vessels utilizing the Association Rule Mining method. In this respect, 374 offshore vessel accident reports are analyzed using the Apriori algorithm. In addition, Logistic Regression analysis is performed to examine the factors affecting accident severity. 'offshore support vessels', 'non-FOC', 'vessels over 12 years old', and 'serious accident' were the most frequent items in the formation of rules. Logistic Regression demonstrates that items in association rules have a higher probability of serious accidents in variables such as total loss, vessel age, type, and flag. However, in terms of vessel type, 'oil exploration and drilling vessels' and 'offshore construction vessels' are determined to be riskier than 'offshore support vessels'. The results can be helpful for offshore operators and relevant authorities to understand the accidents better and to take preventive measures.