Listar por tema "Bayesian inference"
Mostrando ítems 21-31 de 31
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A Nonlinear Model Inversion Method for Joint System Parameter, Noise, and Input Identification of Civil Structures
(2017)This paper presents a framework for nonlinear system identification of civil structures using sparsely measured dynamic output response of the structure. Using a sequential maximum likelihood estimation (MLE) approach, the ... -
Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost
(2022)This paper proposes an optimal sensor placement (OSP) framework for parameter estimation, virtual sensing, and condition monitoring using information theory. The framework uses a Bayesian OSP method combined with modal ... -
Optimal sensor placement for response predictions using local and global methods
(2020)A Bayesian framework for model-based optimal sensor placement for response predictions is presented. Our interest lies in determining the parameters of the model in order to make predictions about a particular response ... -
Optimal sensor placement for response reconstruction in structural dynamics
(2020)A framework for optimal sensor placement (OSP) for response reconstruction under uncertainty is presented based on information theory. The OSP is selected as the one that maximizes an expected utility function taken as the ... -
Optimization algorithms for system integration
(2008)This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising ... -
Pi 4U: A high performance computing framework for Bayesian uncertainty quantification of complex models
(2015)We present Pi 4U,(1) an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel ... -
Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions
(2019)A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation ... -
Statistics-based Bayesian modeling framework for uncertainty quantification and propagation
(2022)A new Bayesian modeling framework is proposed to account for the uncertainty in the model parameters arising from model and measurements errors, as well as experimental, operational, environmental and manufacturing ... -
Uncertainty calibration of large-order models of bridges using ambient vibration measurements
(2014)A computational efficient Bayesian inference framework based on stochastic simulation algorithms is presented for calibrating the parameters of large-order linear finite element (FE) models of bridges. The effectiveness ... -
A unified sampling-based framework for optimal sensor placement considering parameter and prediction inference
(2021)We present a Bayesian framework for model-based optimal sensor placement. Our interest lies in minimizing the uncertainty on predictions of a particular response quantity of interest, with parameter estimation being an ... -
X-TMCMC: Adaptive kriging for Bayesian inverse modeling
(2015)The Bayesian inference of models associated with large-scale simulations is prohibitively expensive even for massively parallel architectures. We demonstrate that we can drastically reduce this cost by combining adaptive ...