Ship Detention Situation Prediction via Optimized Analytic Hierarchy Process and Naïve Bayes Model

Abstract

<jats:p>Ship detention serves as an obligatory but efficient manner in port state control (PSC) inspection, and accurate ship detention prediction provides early warning information for maritime traffic participants. Previous studies mainly focused on exploiting the relationship between ship factors (i.e., ship age and ship type) and PSC inspection reports. Less attention was paid to identify and predict the correlation between ship fatal deficiency and ship detention event. To address the issue, we propose a novel framework to identify crucial ship deficiency types with an optimized analytic hierarchy process (AHP) model. Then, the Naïve Bayes model is introduced to predict the ship detention probability considering weights of the identified crucial ship deficiency types. Finally, we evaluate our proposed model performance on the empirical PSC inspection dataset. The research findings can help PSC officials easily determine main ship deficiencies, and thus, less time cost is required for implementing the PSC inspection procedure. In that manner, the PSC officials can quickly make ship detention decision and thus enhance maritime traffic safety.</jats:p>

A bibliometric review on maritime inspection analysis: Current and future insights

“…The number of papers per year by the research fields. 68 , Fu et al 74 Mansell 2 , Perepelkin et al 76 , Liying 77 , Mansell 78 , Thurston and Lymbery 79 Silos et al 3 , Lin and Cheng 29 , Heij and Knapp 30 , Bijwaard and Knapp 80 , Boisson 81 Cebi et al 4 , Navas de Maya et al 28 , Grbic et al 82 , Ma 83 Dikis et al 64 , Xue and Tang 84 , Guoqiang and Yunqing 85 , Heij and Knapp 86 , Ishak et al 87 i. The datasets collected based on maritime inspection analysis do not have enough variable types and numbers.…”

“…Qualitative research Mixed methods research Navas de Maya et al 28 , Osman et al 47 , Fu et al 49 , Yan et al 52 , Xiao et al 62 , Dikis et al 64 , Yang et al 67 , Yu et al 68 , Ukic ´Boljat et al 69 , Liu et al 70 Xiao et al 5 , Piniella et al 6 , Akyurek and Bolat 32 , Liou et al 34 , Osman et al 36 , Bielic ´et al 39 , Randic ´et al 45 , Akyurek and Bolat 71 , Knapp and van de Velden 72 , Chi and Jun 73 Cebi et al 4 , Yang et al 23 , Lin and Cheng 29 , Wang et al 33 , Sotiralis et al 35 , Graziano et al 38 , Wu et al 54 , Knapp and Franses 63 , Fu et al 74 , Cariou et al 75 Figure 12. The number of papers per year by the research fields.…”

Deficiency Analysis Identified in PSC Inspections Using Event Tree Analysis

“…In the Paris MoU inspection regime, "ship age" and "ship type" parameters have great importance in the definition of the ship risk profile [25][26][27][28][29][30][31][32][33]. When calculating the ship risk profile, 2 points are given if the ship type is in high risk group and 1 point is given if the ship age is in high risk group.…”

An Interpretable Aid Decision-Making Model for Flag State Control Ship Detention Based on SMOTE and XGBoost

“…They established a model to identify vulnerable PSC ships through logistic regression analysis, and used the safety inspection data from 946 ships for verification. Fu, J. et al (2020) [15] put forward a novel framework to optimize an analytic hierarchy process (AHP) model for identifying the main types of vessel defects, and introduced a simple Bayesian model for identifying the weighting of critical defects to predict the probability of ship detention. Finally, the PSC inspection dataset was used to model the performance test, and the results proved that the method could be applied to real ship safety inspection work to assist PSCOs making detention decisions, and therefore reduce the time and cost needed for PSC inspections.…”