Sfoglia per Soggetto "Bayesian learning"
Items 1-4 di 4
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Data features-based likelihood-informed Bayesian finite element model updating
(2019)A new formulation for likelihood-informed Bayesian inference is proposed in this work based on probability models introduced for the features between the measurements and model predictions. The formulation applies to both ... -
Data-driven uncertainty quantification and propagation in structural dynamics through a hierarchical Bayesian framework
(2020)In the presence of modeling errors, the mainstream Bayesian methods seldom give a realistic account of uncertainties as they commonly underestimate the inherent variability of parameters. This problem is not due to any ... -
Hierarchical Bayesian learning framework for multi-level modeling using multi-level data
(2022)A hierarchical Bayesian learning framework is proposed to account for multi-level modeling in structural dynamics. In multi-level modeling the system is considered as a hierarchy of lower-level models, starting at the ... -
Hierarchical Bayesian operational modal analysis: Theory and computations
(2020)This paper presents a hierarchical Bayesian modeling framework for the uncertainty quantification in modal identification of linear dynamical systems using multiple vibration data sets. This novel framework integrates the ...