Scenario deduction model of unconventional emergency based on dynamic bayesian network

The unclear evolution path and complex development of unconventional emergency could make it difficult for decision-makers to make right decisions. A model based on the dynamic Bayesian network was proposed to solve the key scenario deduction problems of unconventional emergency. In this model, the scenario evolution law of unconventional emergency was first analyzed to formulate the four factors including scenario situation(S), disposal target (T), disposal measure (M) and evolution (E). Then the scenario evolution path was performed based on the four factors. Finally, the state probabilities of corresponding node variables were calculated by using the joint probability formula. For the purpose of illustration and verification, the case of Dalian “7·16” oil depot fire and explosion accident was presented. The results showed that the evolution path follows oil pipeline explosion, oil tank explosion and fire, and oil spill and offshore pollution, whose probabilities are respectively 90.2%, 84.1% and 80.3%. Thus, it could be concluded that the proposed dynamic Bayesian network is both reasonable and feasible.