AL
Adolphus Lye
Authored
4 records found
This tutorial paper reviews the use of advanced Monte Carlo sampling methods in the context of Bayesian model updating for engineering applications. Markov Chain Monte Carlo, Transitional Markov Chain Monte Carlo, and Sequential Monte Carlo methods are introduced, applied to d ...
An efficient and robust sampler for Bayesian inference
Transitional Ensemble Markov Chain Monte Carlo
Bayesian inference is a popular approach towards parameter identification in engineering problems. Such technique would involve iterative sampling methods which are often robust. However, these sampling methods often require significant computational resources and also the tun ...
One of the advanced Monte Carlo techniques employed to perform Bayesian model updating on the epistemic model parameter(s) is the Transitional Markov Chain Monte Carlo sampler. A key characteristic in its sampling approach involves the use of "transitional" distributions to allow
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Several on-line identification approaches have been proposed to identify parameters and evolution models of engineering systems and structures when sequential datasets are available via Bayesian inference. In this work, a robust and “tune-free” sampler is proposed to extend one o
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