Fig 1.
The schematic view of the proposed DQCPEA.
Table 1.
Ship type classifications and corresponding code IDs.
Fig 2.
Ship type deficiency analysis.
(a) The histograms show Stp, Def and Det under 23 different ship types. (b) The curves show Ave-Def, Ave-Det and Def/Det under 23 different ship types.
Fig 3.
(a) The histograms show Stp, Def and Det within 1960s to 2010s. (b) The curves show Ave-Def, Ave-Det and Def/Det within 1960s to 2010s.
Fig 4.
Ship deadweight deficiency analysis.
(a) The histograms show Stp, Def and Det under different levels of deadweight. (b) The curves show Ave-Def, Ave-Det and Def/Det under different levels of deadweight.
Fig 5.
Ship gross tonnage deficiency analysis.
(a) The histograms show Stp, Def and Det under different levels of gross tonnage. (b) The curves show Ave-Def, Ave-Det and Def/Det under different levels of gross tonnage.
Table 2.
Parent ship deficiency code IDs and corresponding defective items.
Table 3.
Frequent itemsets exploration under different combinations of α and β for the parent ship deficiency analysis.
Fig 6.
Correlation exploration network of items of frequent itemsets in parent deficiency category with different α and β setups.
(a) α = 0.20, β 0.5. (b) α = 0.25, β = 0.5. (c) α = 0.2, β = 0.6. (d) α = 0.25, β = 0.6.
Table 4.
The details of deficiency subcategory classification.
Table 5.
Frequent itemsets exploration under different combinations of α and β for deficiency subcategory correlation analysis.
Table 6.
Ship deficiency subcategory code IDs and corresponding defective items.
Fig 7.
Correlation exploration network of items of frequent itemsets in ship deficiency subcategories with different α and β setups.
(a) (α = 0.10, β = 0.5). (b). (α = 0.10, β = 0.6). (c) (α = 0.15, β = 0.5) or (α = 0.15, β = 0.6).