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Bayesian Network Model of Maritime Safety Management
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School of Science |
Master's thesis
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TU-22
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en
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98
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Abstract
Maritime traffic operations encompass several activities that, due to their general characteristics, compromise the safety of the personnel at sea and ashore.
Maritime safety management and its derived standards have constantly reviewed, evaluated and improved the general conditions of the mentioned operations.
Nevertheless, the correct use and application of maritime safety management standards will always depend on the particular interpretation by maritime safety experts.
Thus, the combination of maritime safety standards and the knowledge of maritime experts is and will always be an important factor that influences the course of safety management in maritime traffic operations.
This thesis provides a new proposal for the modeling of maritime safety management: the Bayesian Network Model of Maritime Safety Management.
The model integrates the most relevant components of maritime safety management within the content of maritime safety management standards, the interpretation of safety management by maritime safety experts, and several practical indicators of the maritime safety performance.
In order to model the safety management in maritime traffic, this study has adopted Bayesian networks methodology due to its remarkable characteristics for modeling uncertain expert knowledge.
Furthermore, the proposed model has also been tested through a practical application in the local shipping industry.
The aims during this test were to analyze dependencies and logic of the components of the model, and also to collect expert knowledge and information regarding to current maritime safety management practices.
Thus, the obtained results in this thesis propose and evaluate the possibility of using Bayesian networks as a tool to model and analyze the safety management of maritime traffic operations.