gPCE-Based Stochastic Inverse Methods: A Benchmark Study from a Civil Engineer’s Perspective
In civil and mechanical engineering, Bayesian inverse methods may serve to calibrate the uncertain input parameters of a structural model given the measurements of the outputs. Through such a Bayesian framework, a probabilistic description of parameters to be calibrated can be obtained; this approac...
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Autores principales: | Filippo Landi, Francesca Marsili, Noemi Friedman, Pietro Croce |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/e26667696919492baf7d90941c77e856 |
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