作者: Michelle Bensi , Armen Der Kiureghian , Daniel Straub
关键词: Data mining 、 Component (UML) 、 Risk assessment 、 Construct (python library) 、 Bayesian network 、 Influence diagram 、 Hazard (logic) 、 Engineering 、 Risk analysis 、 Heuristic
摘要: AbstractThe Bayesian network (BN) and influence diagram (ID) are used to develop a framework for post-earthquake risk assessment decision making infrastructure systems. The BN is model the earthquake hazard component system performance, update these models probabilistically in light of information gained from ground motion or structural health-monitoring sensors, observation states. extended by addition utility nodes construct an ID, which regarding type inspection perform setting operational levels components. A value-of-information heuristic proposed determine optimal temporal sequence inspections. methodology demonstrated its application hypothetical segment California high-speed rail system. Although focus this paper on hazard, can be f...