概率逻辑
贝叶斯网络
危害
地震灾害
细分
计算机科学
地震风险
地震学
中国
计算
贝叶斯概率
条件概率
地质学
工程类
算法
地理
土木工程
人工智能
统计
数学
考古
有机化学
化学
摘要
Abstract Bayesian network (BN) has important applications in disaster risk analysis due to its unique causal structure and probabilistic characteristics. This research begins with a detailed introduction to probabilistic seismic hazard analysis (PSHA) for China, and the utilization of BN-based modeling for seismic hazard and risk assessment. Subsequently, a comprehensive theoretical exposition of PSHA for China based on BN is presented. This includes a clear explanation of the three-level subdivision of seismic sources and the employment of the elliptical ground-motion model (GMM) in China. Regarding BN modeling, the values, conditional probabilities, and the impact of subdivisions of the nodes are carefully discussed with the assistance of a specific example from China. The advantages of BN in terms of both holistic and probabilistic computation are then demonstrated through the disaggregation of seismic hazard and various sensitivity analyses. Finally, the article concludes by summarizing its content, highlighting the advantages of BN, and outlining future work.
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