This paper summarises the advanced techniques adopted for the analysis of human and
organizational factors, which are the predominant factors in maritime accidents, and the …

Over the past 50 years, research in maritime accidents has undergone a series of
fundamental changes. Understanding the evolution of these changes can help maritime …

A data-driven Bayesian network (BN) is used to investigate the effect of human factors on
maritime safety through maritime accident analysis. Its novelties consist of (1) manual …

The Bayesian network (BN) is a powerful model for probabilistic knowledge representation
and inference and is increasingly used in the field of reliability evaluation. This paper …

The rapid development of the ship** industry requires the use of large vessels carrying
high-volume cargoes. Accidents incurred by these vessels can lead to a heavy loss of life …

Abstract The use of Bayesian Belief Networks (BBNs) in risk analysis (and in particular
Human Reliability Analysis, HRA) is fostered by a number of features, attractive in fields with …

Over the past decade the number of maritime transportation accidents has fallen. However,
as ship** vessels continue to increase in size, one single incident, such as the oil spills …

Human factors are widely regarded to be highly contributing factors to maritime accident
prevention system failures. The conventional methods for human factor assessment …

Human error is a significant factor triggering oil tanker collisions. Drawbacks jeopardizing
the effectiveness of human error analysis from traditional studies are spotted. This study …

This article proposes a modified cognitive reliability and error analysis method (CREAM) for
estimating the human error probability in the maritime accident process on the basis of an …