Low rank surrogates for fuzzy‐stochastic partial differential equations
Abstract: We consider a particular fuzzy‐stochastic PDE depending on the interaction of probabilistic and non‐probabilistic (via fuzzy arithmetic in terms of possibility theory) influences. Such a combination is beneficial in an engineering context, where aleatoric and epistemic uncertainties appear simultaneously. The fuzzy‐stochastic dependence is described in a high‐dimensional parameter space, thus easily leading to an exponential complexity in practical computations. To alleviate this severe obstacle, a compressed low‐rank approximation in form of Hierarchical Tucker representation of the desired parametric quantity of interest is derived. The performance of the proposed model order reduction approach is demonstrated.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Low rank surrogates for fuzzy‐stochastic partial differential equations ; volume:19 ; number:1 ; year:2019 ; extent:2
Proceedings in applied mathematics and mechanics ; 19, Heft 1 (2019) (gesamt 2)
- Creator
- DOI
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10.1002/pamm.201900376
- URN
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urn:nbn:de:101:1-2022072208181994566326
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:21 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Gruhlke, Robert
- Eigel, Martin
- Moser, Dieter
- Grasedyck, Lars
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