Ergebnisse für: Reduced Basis Method
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This book provides a basic introduction to reduced basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs) arising from engineering and applied sciences, such as PDEs depending on several parameters and PDE-constrained optimization. The book pres...
This book provides a basic introduction to reduced basis (RB) methods for problems involving the repeated solution of partial differential equations (PDEs) arising from engineering and applied sciences, such as PDEs depending on several parameters and PDE-constrained optimization. The book pres...
Simulations provide support in understanding and predicting the behavior of systems in engineering and science. However, if the problem setting is rather complex the computational costs for performing simulations can be extremely high. In those cases model order reduction techniques can help to lowe...
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced r...
The volume features high-quality papers based on the presentations at the ICOSAHOM 2020+1 on spectral and high order methods. The carefully reviewed articles cover state of the art topics in high order discretizations of partial differential equations.
The volume presents a wide range of topics in...
This thesis is about model order reduction methods for parametric and high-dimensional optimal feedback control problems for both linear and nonlinear systems.
In the first part of this work, the reduced basis method for the algebraic Riccati equation is introduced. This method consists of the low-...
The volume features high-quality papers based on the presentations at the ICOSAHOM 2020+1 on spectral and high order methods. The carefully reviewed articles cover state of the art topics in high order discretizations of partial differential equations.
The volume presents a wide range of topics in...
The volume features high-quality papers based on the presentations at the ICOSAHOM 2020+1 on spectral and high order methods. The carefully reviewed articles cover state of the art topics in high order discretizations of partial differential equations.
The volume presents a wide range of topics in...
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced r...
This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947.
Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This ...
This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947.
Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This ...
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced r...
This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947.
Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This ...
The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the...