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Stochastic reduced order models for inverse problems under uncertainty
This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrai...
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Publicado no: | Comput Methods Appl Mech Eng |
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Main Authors: | , , |
Formato: | Artigo |
Idioma: | Inglês |
Publicado em: |
2015
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Assuntos: | |
Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4281272/ https://ncbi.nlm.nih.gov/pubmed/25558115 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.cma.2014.11.021 |
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