Back to Search
Start Over
Reduced Collocation Methods: Reduced Basis Methods in the Collocation Framework
- Publication Year :
- 2012
-
Abstract
- In this paper, we present the first reduced basis method well-suited for the collocation framework. Two fundamentally different algorithms are presented: the so-called Least Squares Reduced Collocation Method (LSRCM) and Empirical Reduced Collocation Method (ERCM). This work provides a reduced basis strategy to practitioners who {prefer} a collocation, rather than Galerkin, approach. Furthermore, the empirical reduced collocation method eliminates a potentially costly online procedure that is needed for non-affine problems with Galerkin approach. Numerical results demonstrate the high efficiency and accuracy of the reduced collocation methods, which match or exceed that of the traditional reduced basis method in the Galerkin framework.
- Subjects :
- Numerical Analysis
Mathematical optimization
Collocation
Basis (linear algebra)
Applied Mathematics
General Engineering
Numerical Analysis (math.NA)
010103 numerical & computational mathematics
01 natural sciences
Least squares
Theoretical Computer Science
010101 applied mathematics
Computational Mathematics
Computational Theory and Mathematics
Collocation method
FOS: Mathematics
Orthogonal collocation
Mathematics - Numerical Analysis
0101 mathematics
65M60, 65N30
Greedy algorithm
Galerkin method
Software
Mathematics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....b81434daaaf5b436cbc6b74458518053