Bayesian updating with two-step parallel Bayesian optimization and quadrature

Kitahara M.; Dang C.; Beer M.

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Bayesian updating with two-step parallel Bayesian optimization and quadrature

机译：Bayesian updating with two-step parallel Bayesian optimization and quadrature

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? 2022 Elsevier B.V.This work proposes a Bayesian updating approach, called parallel Bayesian optimization and quadrature (PBOQ). It is rooted in Bayesian updating with structural reliability methods (BUS) and offers a coherent Bayesian approach for the BUS analysis by assuming Gaussian process priors. The first step of the method, i.e., parallel Bayesian optimization, effectively explores a constant c in BUS by a novel parallel infill sampling strategy. The second step (parallel Bayesian quadrature) then infers the posterior distribution by another parallel infill sampling strategy using subset simulation. The proposed approach enables to make the fullest use of prior knowledge and parallel computing, resulting in a substantial reduction of the computational burden of model updating. Four numerical examples with varying complexity are investigated for demonstrating the proposed method against several existing methods. The results show the potential benefits by advocating a coherent Bayesian fashion to the BUS analysis.

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《Computer Methods in Applied Mechanics and Engineering》 |2023年第1期|1187-1207|共21页
作者
Kitahara M.; Dang C.; Beer M.;
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作者单位

Institute for Risk and Reliability Leibniz Universit?t Hannover||Institute for Risk and Uncertainty University of Liverpool||International Joint Research Center for Resilient Infrastructure & International Joint Research Center for Engineering Reliability;

Institute for Risk and Reliability Leibniz Universit?t Hannover;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
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关键词
Bayesian model updating; Bayesian optimization; Bayesian quadrature; Gaussian process; Parallel computing;

Bayesian updating with two-step parallel Bayesian optimization and quadrature

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