Bayesian Model for Constructing Factors Affecting Ship Accidents and Accident Consequences

Abstract

Global economic growth has stimulated the growth of international trade, leading to more maritime transport activities. However, in a complex and high-risk environment at sea, heavy ship accidents are difficult to eliminate. In order to prevent ship accidents more effectively, this paper attempts using Bayesian network model to construct the dependence relationship among ship’s inherent properties (ship age, ship flag, classification society, ship size and types), Port State Control (PSC) inspection defect items, accident and consequences. In addition, the model can be continuously updated as the external environment changes.