A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis

This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) sampling. Substantial computational speedu...

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Detalles Bibliográficos
Autores principales: Warner, James E., Bomarito, Geoffrey F., Hochhalter, Jacob D., Leser, William P., Leser, Patrick E., Newman, John A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376618/
https://www.ncbi.nlm.nih.gov/pubmed/32704401

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7376618/
https://www.ncbi.nlm.nih.gov/pubmed/32704401

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