Neural network ensembles and uncertainty estimation for predictions of inelastic mechanical deformation using a finite element method-neural network approach

Neural network ensembles and uncertainty estimation for predictions of inelastic mechanical deformation using a finite element method-neural network approach

The finite element method (FEM) is widely used to simulate a variety of physics phenomena. Approaches that integrate FEM with neural networks (NNs) are typically leveraged as an alternative to conducting expensive FEM simulations in order to reduce the computational cost without significantly sacrif...

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Bibliographic Details
Main Authors: Guy L. Bergel, David Montes de Oca Zapiain, Vicente Romero
Format: Article
Language:English
Published: Cambridge University Press 2023-01-01
Series:Data-Centric Engineering
Subjects:
Bayesian neural networks
finite element method
neural network ensembles
surrogate models
uncertainty quantification
variational Bayesian inference
Online Access:https://www.cambridge.org/core/product/identifier/S2632673623000175/type/journal_article

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https://www.cambridge.org/core/product/identifier/S2632673623000175/type/journal_article

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