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Structural Analysis with Fuzzy Data and Neural Network Based Material Description.
- Source :
- Computer-Aided Civil & Infrastructure Engineering; Oct2012, Vol. 27 Issue 9, p640-654, 15p, 4 Diagrams, 11 Graphs
- Publication Year :
- 2012
-
Abstract
- In the article, a new approach is presented utilizing artificial neural networks for uncertain time-dependent structural behavior. Recurrent neural networks (RNNs) for fuzzy data can be trained by uncertain experimental data to describe arbitrary stress-strain-time dependencies. The benefit is a generalized formulation, which can be applied to describe the behavior of several materials without definition of a specific material model. Model-free material descriptions can be used as numerical efficient material formulations within the finite element method. To perform fuzzy or fuzzy stochastic finite element analyses, a new approach is introduced. An -level optimization is utilized for signal computation and training of RNNs for fuzzy data. The applicability is demonstrated by means of examples. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10939687
- Volume :
- 27
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Computer-Aided Civil & Infrastructure Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 79650125
- Full Text :
- https://doi.org/10.1111/j.1467-8667.2012.00779.x