Bayesian inference of COVID-19 spreading rates in South Africa
The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has
highlighted the need for performing accurate inference with limited data. Fundamental to the …
highlighted the need for performing accurate inference with limited data. Fundamental to the …
Finite element model updating using the shadow hybrid Monte Carlo technique
Recent research in the field of finite element model updating (FEM) advocates the adoption
of Bayesian analysis techniques to dealing with the uncertainties associated with these …
of Bayesian analysis techniques to dealing with the uncertainties associated with these …
Finite element model updating using fish school search and volitive particle swarm optimization
I Boulkaibet, L Mthembu… - Integrated Computer …, 2015 - content.iospress.com
A customized version of Fish School Search (FSS) algorithm and the innovative volitive
operator of FSS (which is incorporated into the regular particle swarm optimization (PSO) …
operator of FSS (which is incorporated into the regular particle swarm optimization (PSO) …
Finite element model updating using Hamiltonian Monte Carlo techniques
Bayesian techniques have been widely used in finite element model (FEM) updating. The
attraction of these techniques is their ability to quantify and characterize the uncertainties …
attraction of these techniques is their ability to quantify and characterize the uncertainties …
On data-driven management of the COVID-19 outbreak in South Africa
The rapid spread of the novel coronavirus (SARS-CoV-2) has highlighted the need for the
development of rapid mitigating responses under conditions of extreme uncertainty. While …
development of rapid mitigating responses under conditions of extreme uncertainty. While …
Prediction error variances in Bayesian model updating employing data sensitivity
K Prajapat, S Ray-Chaudhuri - Journal of Engineering Mechanics, 2016 - ascelibrary.org
Efficiency of a Bayesian model updating algorithm is greatly affected by the choice of
variance of prediction error models of different data points (evidence) used for model …
variance of prediction error models of different data points (evidence) used for model …
Gibbs sampling for damage detection using complex modal data from multiple setups
This paper presents a novel Gibbs sampling approach for structural health monitoring (SHM)
with detection of structural changes/damages using incomplete complex modal data …
with detection of structural changes/damages using incomplete complex modal data …
A differential evolution Markov chain Monte Carlo algorithm for Bayesian model updating
The use of the Bayesian tools in system identification and model updating paradigms has
been increased in the last 10 years. Usually, the Bayesian techniques can be implemented …
been increased in the last 10 years. Usually, the Bayesian techniques can be implemented …
Finite element model updating using a shuffled complex evolution Markov chain algorithm
In this paper, a probabilistic-based evolution Markov chain algorithm is used for updating
finite element models. The Bayesian approaches are well-known algorithms used for …
finite element models. The Bayesian approaches are well-known algorithms used for …
Finite element model updating using an evolutionary Markov chain Monte Carlo algorithm
One challenge in the finite element model (FEM) updating of a physical system is to estimate
the values of the uncertain model variables. For large systems with multiple parameters this …
the values of the uncertain model variables. For large systems with multiple parameters this …