The Effect of Shipowners’ Effort in Vessels Accident: A Bayesian Network Approach

This paper presents an innovative approach to integrate logistic regression and Bayesian Network together into risk assessment. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilized in other sectors. Applications of the use of Bayesian networks as a modeling tool in maritime applications have recently been demonstrated widely. A common criticism of the Bayesian approach is that it requires too much information in the form of prior probabilities. And that this information is often difficult, if not impossible, to obtain in risk assessment (Yang et al., 2008). Traditional and the most common way to estimate the prior probability of accidents is by expert estimation. There are some typical problems associated with using the subjective probability, provided by expert, as a measure of uncertainty in risk analysis. In this research, a binary logistic regression method is used to provide input for a BN, making use of different resources of data in maritime accidents.