.png){kind=icon}
返回
Efficient Bayesian model updating for dynamic systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ress.2023.109294.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Bayesian updating has been a successful tool for model calibration in uncertainty analysis, especially in reliability analysis. However, Bayesian updating of dynamic systems with high-dimensional output remains challenging work due to the heavy computational burden associated with evaluating a high-dimensional likelihood function. In this case, even the efficient surrogate model methods can fall short of their expected potential. To solve this problem, this paper develops a novel Bayesian updating framework for dynamic systems based on principal component analysis (PCA), which can significantly reduce the output dimension and overcome the curse of dimension. In the proposed framework, a new likelihood function is constructed based on the lowdimensional output principal components (PCs), and it is analytically proved that the new likelihood function can provide the equivalent likelihood measures to the original one. In this way, any common Bayesian updating method can be applied in the low dimensional PC space by using the new likelihood function. To further improve the efficiency, an efficient Bayesian updating algorithm is proposed in the PCA-based framework, which adopts adaptive Bayesian updating with structural reliability methods (aBUS) and the Kriging model. Finally, four examples are investigated to test the validity of the proposed method.
Keyword:
Bayesian updating
Principal component analysis (PCA)
Model calibration
Kriging model
Uncertainty analysis
期刊
R
IF:
11
论文数:
9.0K
被引数:
4.2W
机构
引用论文
.png){kind=icon}
Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation
PREAI
分享收藏Transitional markov chain monte carlo method for Bayesian model updating, model class selection, and model averaging用于贝叶斯模型更新，模型类选择和模型平均的过渡马尔可夫链蒙特卡洛方法
PREAI
分享收藏Sequential Bayesian inference for Weibull distribution parameters with initial hyperparameter optimization for system reliability estimation用于系统可靠性估计的具有初始超参数优化的Weibull分布参数的序贯贝叶斯推断
OAAI
OAAI分享收藏
Bayesian updating with adaptive, uncertainty-informed subset simulations: High-fidelity updating with multiple observations具有自适应不确定性信息子集模拟的贝叶斯更新: 具有多个观测值的高保真更新OAAI
OAAI分享收藏Bayesian updating of solar panel fragility curves and implications of higher panel strength for solar generation resilience太阳能电池板脆弱性曲线的贝叶斯更新以及更高的电池板强度对太阳能发电弹性的影响OAAI
OAAI分享收藏
查看更多内容