Bayesian network model of maritime safety management

Maria Hänninen, Osiris A. Valdez Banda, Pentti Kujala

Research output: Contribution to journalArticleScientificpeer-review

74 Citations (Scopus)

Abstract

This paper presents a model of maritime safety management and its subareas. Furthermore, the paper links the safety management to the maritime traffic safety indicated by accident involvement, incidents reported by Vessel Traffic Service and the results from Port State Control inspections. Bayesian belief networks are applied as the modeling technique and the model parameters are based on expert elicitation and learning from historical data. The results from this new application domain of a Bayesian network based expert system suggest that, although several its subareas are functioning properly, the current status of the safety management on vessels navigating in the Finnish waters has room for improvement; the probability of zero poor safety management subareas is only 0.13. Furthermore, according to the model a good IT system for the safety management is the strongest safety-management related signal of an adequate overall safety management level. If no deficiencies have been discovered during a Port State Control inspection, the adequacy of the safety management is almost twice as probable as without knowledge on the inspection history. The resulted model could be applied to performing several safety management related queries and it thus provides support for maritime safety related decision making.

Original languageEnglish
Pages (from-to)7837-7846
Number of pages10
JournalExpert Systems with Applications
Volume41
Issue number17
DOIs
Publication statusPublished - 1 Dec 2014
MoE publication typeA1 Journal article-refereed

Keywords

  • Bayesian networks
  • Expert elicitation
  • Maritime traffic safety
  • Safety indicators
  • Safety management
  • The ISM Code

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