Research on risk identification and assessment for unmanned aerial vehicle maritime transportation

Le résumé fourni par la source

Aiming at the problem of quantitative risk assessment of UAV maritime transportation system, this paper proposes a dynamic risk assessment method integrating fuzzy set theory and Bayesian network. Firstly, based on the analysis of the whole transportation process, a risk assessment system with 16 secondary indicators is constructed from four dimensions of personnel, equipment, environment and management; secondly, the indicator structure is optimized by the Delphi method, and the triangular fuzzy numbers are used to transform the semantic evaluation of the experts, which is combined with the weighting process to eliminate the subjective ambiguity; lastly, the topological model of Bayesian network is established to analyze the risk conduction paths and realize the probability of the probabilistic reasoning under the uncertainty conditions. reasoning under uncertainty conditions. Case analysis shows that this method can accurately quantify the probability of occurrence of risk events and provide a basis for decision-making in risk prevention and control.

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