Model Order Reduction. Volume 2, Snapshot-Based Methods and Algorithms /

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This second volume focuses on app...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Alfio, Quarteroni (Contribuidor), Andrea, Manzoni (Contribuidor), Andreas, Buhr (Contribuidor), Anthony T., Patera (Contribuidor), Benner, Peter (Editor ), Carmen, Gräßle (Contribuidor), Charbel, Farhat (Contribuidor), Francesco, Ballarin (Contribuidor), Francisco, Chinesta (Contribuidor), Gianluigi, Rozza (Contribuidor), Giovanni, Stabile (Contribuidor), Grivet-Talocia, Stefano (Editor ), J. Nathan, Kutz (Contribuidor), Kathrin, Smetana (Contribuidor), Laura, Iapichino (Contribuidor), Marco, Tezzele (Contribuidor), Martin, Hess (Contribuidor), Michael, Hinze (Contribuidor), Pierre, Ladevèze (Contribuidor), Quarteroni, Alfio (Editor ), Rozza, Gianluigi (Editor ), Schilders, Wil (Editor ), Sebastian, Grimberg (Contribuidor), Silveira, Luís Miguel (Editor ), Stefan, Volkwein (Contribuidor), Steven L., Brunton (Contribuidor), Yvon, Maday (Contribuidor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin ; Boston : De Gruyter, [2020]
Temas:
Mathematical models.
Mathematical models > Evaluation.
Differential equations, Partial.
Engineering mathematics.
Computational physics.
Computersimulation.
Mathematisches Modell.
Ordnungsreduktion.
Modèles mathématiques.
Équations aux dérivées partielles.
Mathématiques de l'ingénieur.
mathematical models.
MATHEMATICS / Numerical Analysis.
Differential equations, Partial
Engineering mathematics
Mathematical models
Mathematical models > Evaluation
Applied mathematics
PROM
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Frontmatter
  • Preface to the second volume of Model Order Reduction
  • Contents
  • 1 Basic ideas and tools for projection-based model reduction of parametric partial differential equations
  • 2 Model order reduction by proper orthogonal decomposition
  • 3 Proper generalized decomposition
  • 4 Reduced basis methods
  • 5 Computational bottlenecks for PROMs: precomputation and hyperreduction
  • 6 Localized model reduction for parameterized problems
  • 7 Data-driven methods for reduced-order modeling
  • Index

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