Non-parametric simulation of non-stationary non-gaussian 3D random field samples directly from sparse measurements using signal decomposition and Markov Chain Monte Carlo (MCMC) simulation
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DOI: 10.1016/j.ress.2020.107087
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Cited by:
- Zhang, Ruijing & Dai, Hongzhe, 2022. "A non-Gaussian stochastic model from limited observations using polynomial chaos and fractional moments," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
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- He, Jingran & Gao, Ruofan & Chen, Jianbing, 2022. "A sparse data-driven stochastic damage model for seismic reliability assessment of reinforced concrete structures," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
- Li, Yang & Xu, Jun, 2024. "Neural network-aided simulation of non-Gaussian stochastic processes," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
- Li, Peiping & Wang, Yu, 2022. "An active learning reliability analysis method using adaptive Bayesian compressive sensing and Monte Carlo simulation (ABCS-MCS)," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
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Keywords
Reliability-based design or analysis; Gibbs sampling; Data-driven method; Bayesian method; Compressive sensing;All these keywords.
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