Data Fusion of Maritime Incident Databases with Dempster–Shafer Theory

Although a huge amount of information is available in all kinds of marine safety databases, only a small part can be used directly. The disorganized information from different sources leads to a mixture of format and definition. In the work reported in this paper, the Dempster–Shafer theory (DST) of evidence was applied to combine evidence (i.e., a piece of information that supports a claim) from different sources. The method is regarded as a generalization of the Bayesian theory and can avoid two difficulties in classical probability theory: handling the conflicting information and assigning prior probabilities. The work of data fusion was demonstrated first by a decision fusion problem that involved the reconciliation of contradictory expert reports. The DST can provide a decision maker with a comprehensive result through the combination of different experts’ opinions. Second, fusion was conducted of two representative maritime incident databases: that of the Global Integrated Shipping Information System and that of the International Chamber of Commerce. Although the records in the databases had some defects (e.g., disorder, error, contradiction), the DST was able to work effectively and calculate an uncertainty interval of incident.