Earthquake disasters can not only trigger secondary disasters such as geological disasters and fires, but also lead to a series of derivative consequences such as traffic interruptions, building collapses, and the destruction of urban lifelines. This phenomenon is known as the earthquake disaster chain. To grasp the objective laws of the evolution of the earthquake disaster chain and effectively prevent the risks of the earthquake disaster chain, a Bayesian network based on combined parameter estimation for earthquake disaster chain scene evolution was proposed in this paper. First, the pregnancy disaster environment and adverse consequences were incorporated into the public safety triangle model to refine the disaster chain scenario set. Second, the Cross Impact Analysis-Interactive Structural Model was introduced for the scenario deduction of the disaster chain, and a Bayesian network-based earthquake disaster chain scenario evolution model was constructed. Finally, game theory was applied to combine the parameters obtained from the improved Dempster-Shafer evidence theory and the expectation-maximization algorithm, resulting in a new parameter estimation algorithm—combined parameter estimation. For the earthquake disaster chain, we verified the effectiveness of the proposed method and proposed emergency management recommendations for the earthquake disaster chain. The results showed that the proposed method can comprehensively demonstrate the evolution process of the earthquake disaster chain, and for different earthquake risks and different earthquake disaster chains, grasping key emergency decisions can effectively reduce the likelihood of adverse consequences.
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Zhang et al. (Tue,) studied this question.
synapsesocial.com/papers/69a760a7c6e9836116a2d9aa — DOI: https://doi.org/10.1061/nhrefo.nheng-2442
L Zhang
Wei Wang
Hebei University of Engineering
Qianqian Guo
Natural Hazards Review
Beijing University of Technology
Beijing University of Civil Engineering and Architecture
North China University of Water Resources and Electric Power
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