A novel adaptive importance sampling algorithm for Bayesian model updating

•A novel adaptive importance sampling-based Bayesian model updating algorithm is proposed.•A stopping criteria called N-ESS is adopted to terminate the adaptive procedure to reduce computational efforts.•The proposed algorithm successfully constructs the importance sampling density that resembles th...

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Vydané v:	Structural safety Ročník 97; s. 102230
Hlavní autori:	Xiao, Xiong, Li, Quanwang, Wang, Zeyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier Ltd 01.07.2022 Elsevier BV
Predmet:	Adaptive algorithms Adaptive importance sampling Adaptive sampling Algorithms Bayesian analysis Bayesian updating Chloride-induced concrete corrosion Computer applications Corrosion tests Cross entropy Density Entropy (Information theory) Gaussian mixture Importance sampling Markov chains Mathematical models Model updating Population Monte Carlo Sampling System identification Bayesian updating Cross entropy Population Monte Carlo Chloride-induced concrete corrosion Gaussian mixture Adaptive importance sampling Model updating
ISSN:	0167-4730, 1879-3355
On-line prístup:	Získať plný text
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