Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model

To enhance the accuracy of finite element model simulation, a model updating method based on Bayesian theory is proposed, and the updating efficiency is improved by integrating improved Markov chain Monte Carlo (MCMC) algorithm and surrogate model. A radial basis function (RBF) surrogate model is co...

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Bibliografiska uppgifter

Huvudupphov:	MIAO Ji, DUAN Liping, LIU Jiming, LIN Siwei, ZHAO Jincheng
Materialtyp:	Artigo
Språk:	Chinês
Utgiven:	Editorial Office of Journal of Shanghai Jiao Tong University 2025-08-01
Serie:	Shanghai Jiaotong Daxue xuebao
Ämnen:	model updating bayesian theory markov chain monte carlo (mcmc) whale optimization algorithm (woa) surrogate model
Länkar:	https://xuebao.sjtu.edu.cn/article/2025/1006-2467/1006-2467-59-8-1114.shtml
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