What is Markov chain Monte Carlo based Bayesian method?
Markov chain monte carlo-based bayesian method for structural model updating and damage detection S. He, C.T. Ng A probabilistic approach for quantitative identification of multiple delaminations in laminated composite beams using guided waves S. He, C.T. Ng Guided wave-based identification of multiple cracks in beams using a bayesian approach
What is Monte Carlo based Bayesian model updating?
An adaptive sequential Monte Carlo method for approximate Bayesian computation Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced markov chain monte carlo simulation algorithm Markov chain monte carlo-based bayesian method for structural model updating and damage detection
What is a motif in Markov chain Monte Carlo?
Specifically, a motif is defined not only in terms of specific sites characterized by amino acid frequency vectors, but also as a combination of secondary characteristics such as hydrophobicity, polarity, etc. Markov chain Monte Carlo methods are proposed to search for a motif pattern with high posterior probability under the new model.
How is uncertainty propagation based on a Markov chain sample?
A new formulation has been developed based on the Markov chain sample to integrate modal analysis, model updating and model class selection. Uncertainty propagation has been done using this formulation. ASMC has been improved with a new formulation that calculates the model class evidence.
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