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    Active Learning of Small Failure Probabilities of Highly Nonstationary Geotechnical Systems by Adaptive Bayesian Compressive Sensing and Subset Simulation 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 001:;page 04024083-1
    Author(s): Peiping Li
    Publisher: American Society of Civil Engineers
    Abstract: Estimating small failure probabilities in complex geotechnical systems with highly nonstationary responses and time-consuming models is a significant challenge. The nonparametric adaptive Bayesian compressive sensing Monte ...
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    Development of an Efficient Response Surface Method for Highly Nonlinear Systems from Sparse Sampling Data Using Bayesian Compressive Sensing 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 004:;page 04021050-1
    Author(s): Peiping Li; Yu Wang
    Publisher: ASCE
    Abstract: A main challenge for risk assessment on geotechnical systems is the computational effort required when stochastic sampling methods are used. Because the deterministic models used for geotechnical systems are often complicated ...
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