Abstract
Early warning on the ship deficiency is crucial for enhancing maritime safety, improving maritime traffic efficiency, reducing ship fuel consumption, etc. Previous studies focused on the ship deficiency exploration by mining the relationships between the ship physical deficiencies and the port state control (PSC) inspection results with statistical models. Less attention was paid to discovering the correlation rules among various parent ship deficiencies and subcategories. To address the issue, we proposed an improved Apriori model to explore the intrinsic mutual correlations among the ship deficiencies from the PSC inspection dataset. Four typical ship property indicators (i.e., ship type, age, deadweight and gross tonnage) were introduced to analyze the correlations for the ship parent deficiency categories and subcategories. The findings of our research can provide basic guidelines for PSC inspections to improve the ship inspection efficiency and maritime safety.
Highlights
Port state control (PSC) inspection is performed to ensure maritime traffic safety, improve the maritime efficiency, etc
Our contributions can be described as follows: (1) we performed the statistical analysis on the ship detention cases with the historical port state control (PSC) data and identified the ship deficiency types that are closely related to the ship detention events; (2) we proposed an improved Apriori model to quantify the correlations among various ship deficiencies of triggering ship detention events; (3) we qualitatively explored the ship detention risk from the perspective of ship profiles and ship subcategory deficiencies
According to the rule of thumb, we introduce six statistical indicators to quantitatively analyze the relationship ship deficiency triggering factors: ship type percentage (Stp), deficiency percentage (Def), detention percentage (Det), average deficiency number (Ave-Def), average detention number (Ave-Det), and deficiency number per detention (Def/Det)
Summary
Port state control (PSC) inspection is performed to ensure maritime traffic safety, improve the maritime efficiency, etc. Several studies focused on analyzing previous maritime accident datasets to collect the PSC priority list, which helps the maritime traffic participants take early-warning activities (e.g., rectifying deficiency at the port or in two weeks) to avoid maritime traffic incidents. Our contributions can be described as follows: (1) we performed the statistical analysis on the ship detention cases with the historical PSC data and identified the ship deficiency types that are closely related to the ship detention events; (2) we proposed an improved Apriori model to quantify the correlations among various ship deficiencies of triggering ship detention events; (3) we qualitatively explored the ship detention risk from the perspective of ship profiles (i.e., parent deficiency) and ship subcategory deficiencies (i.e., child deficiencies).
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