Hochschulschrift
Reduced-Basis Method (RBM) for Non-Affine Elliptic Parametrized PDEs : (Motivated by Optimization in Hydromechanics)
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Ulm, Universität Ulm, Diss., 2012
- Klassifikation
-
Mathematik
- Schlagwort
-
Elliptische Differentialgleichung
Konvektions-Diffusionsgleichung
Partielle Differentialgleichung
Voith-Schneider-Propeller
Optimierung
Optimale Kontrolle
- Ereignis
-
Veröffentlichung
- (wo)
-
Ulm
- (wer)
-
Universität Ulm. Fakultät für Mathematik und Wirtschaftswissenschaften
- (wann)
-
2012
- Urheber
- URN
-
urn:nbn:de:bsz:289-vts-81643
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:50 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Hochschulschrift
Beteiligte
- Tonn, Timo
- Universität Ulm. Fakultät für Mathematik und Wirtschaftswissenschaften
Entstanden
- 2012
Ähnliche Objekte (12)
Deep Neural Networks motivated by PDEs
Affine invariant adaptive Newton codes for discretized PDEs
Fast optimised wavelet methods for control problems constrained by elliptic PDEs
Weighted reduced basis methods for parabolic PDEs with random input data
Reduced basis methods for quasilinear PDEs and applications to electrical machines
Sensitivity Analysis of Optimal Control for a class of parabolic PDEs motivated by Model Predictive Control
Stability of low-rank tensor representations and structured multilevel preconditioning for elliptic PDEs
Optimal control of semilinear elliptic PDEs with state constraints - numerical analysis and implementation
ε-dimension in infinite dimensional hyperbolic cross approximation and application to parametric elliptic PDEs
A deep neural network algorithm for semilinear elliptic PDEs with applications in insurance mathematics
Besov regularity of elliptic and parabolic PDEs with inhomogeneous boundary conditions on Lipschitz domains
Adaptive wavelet methods for variational formulations of nonlinear elliptic PDEs on tensor-product domains
Deep Neural Networks motivated by PDEs
Affine invariant adaptive Newton codes for discretized PDEs
Fast optimised wavelet methods for control problems constrained by elliptic PDEs
Weighted reduced basis methods for parabolic PDEs with random input data
Reduced basis methods for quasilinear PDEs and applications to electrical machines
Sensitivity Analysis of Optimal Control for a class of parabolic PDEs motivated by Model Predictive Control
Stability of low-rank tensor representations and structured multilevel preconditioning for elliptic PDEs
Optimal control of semilinear elliptic PDEs with state constraints - numerical analysis and implementation
ε-dimension in infinite dimensional hyperbolic cross approximation and application to parametric elliptic PDEs
A deep neural network algorithm for semilinear elliptic PDEs with applications in insurance mathematics
Besov regularity of elliptic and parabolic PDEs with inhomogeneous boundary conditions on Lipschitz domains
Adaptive wavelet methods for variational formulations of nonlinear elliptic PDEs on tensor-product domains
Deep Neural Networks motivated by PDEs
Affine invariant adaptive Newton codes for discretized PDEs
Fast optimised wavelet methods for control problems constrained by elliptic PDEs
Weighted reduced basis methods for parabolic PDEs with random input data
Reduced basis methods for quasilinear PDEs and applications to electrical machines
Sensitivity Analysis of Optimal Control for a class of parabolic PDEs motivated by Model Predictive Control
Stability of low-rank tensor representations and structured multilevel preconditioning for elliptic PDEs
Optimal control of semilinear elliptic PDEs with state constraints - numerical analysis and implementation
ε-dimension in infinite dimensional hyperbolic cross approximation and application to parametric elliptic PDEs
A deep neural network algorithm for semilinear elliptic PDEs with applications in insurance mathematics
Besov regularity of elliptic and parabolic PDEs with inhomogeneous boundary conditions on Lipschitz domains