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Using Bayesian networks in analyzing powerful earthquake disaster chains

机译:使用贝叶斯网络分析强大的地震灾害链

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Substantial economic losses, building damage, and loss of life have been caused by secondary disasters that result from strong earthquakes. Earthquake disaster chains occur when secondary disasters take place in sequence. In this paper, we summarize 23 common earthquake disaster chains, whose structures include the serial, parallel, and parallel-serial (dendroid disaster chain) types. Evaluating the probability of powerful earthquake disaster chains is urgently needed for effective disaster prediction and emergency management. To this end, we introduce Bayesian networks (BNs) to assess powerful earthquake disaster chains. The structural graph of a powerful earthquake disaster chain is presented, and the proposed BN modeling method is provided and discussed. BN model of the earthquake-landslides-barrier lakes-floods disaster chain is established. The use of BN shows that such a model enables the effective analysis of earthquake disaster chains. Probability inference reveals that population density, loose debris volume, flooded areas, and landslide dam stability are the most critical links that lead to loss of life in earthquake disaster chains.
机译:强烈地震造成的次生灾害已造成重大的经济损失,建筑物损坏和生命损失。当次生灾害相继发生时,地震灾害链就会发生。在本文中,我们总结了23个常见的地震灾难链,其结构包括串行,并行和并行串行(树状灾难链)类型。为了有效地进行灾难预测和应急管理,迫切需要评估强大地震灾害链的可能性。为此,我们引入了贝叶斯网络(BN)来评估强大的地震灾害链。给出了一个强大的地震灾害链的结构图,并提出和讨论了所提出的BN建模方法。建立了地震-滑坡-屏障湖泊-洪水灾害链的BN模型。 BN的使用表明,这种模型可以有效分析地震灾害链。概率推断表明,人口密度,松散的碎屑量,洪水泛滥和滑坡大坝的稳定性是导致地震灾害链中生命损失的最关键因素。

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