arrow
返回

AN ACCELERATED GREEDY MISSING POINT ESTIMATION PROCEDURE

delete2016-01-01
delete51
delete
OA
AI
R
Ralf Zimmermann *
K
Karen Willcox
DOI:10.1137/15M1042899delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Model reduction via Galerkin projection fails to provide considerable computational savings if applied to general nonlinear systems. This is because the reduced representation of the state vector appears as an argument to the nonlinear function, whose evaluation remains as costly as for the full model. Masked projection approaches, such as the missing point estimation and the (discrete) empirical interpolation method, alleviate this effect by evaluating only a small subset of the components of a given nonlinear term; however, the selection of the evaluated components is a combinatorial problem and is computationally intractable even for systems of small size. This has been addressed through greedy point selection algorithms, which minimize an error indicator by sequentially looping over all components. While doable, this is suboptimal and still costly. This paper introduces an approach to accelerate and improve the greedy search. The method is based on the observation that the greedy algorithm requires solving a sequence of symmetric rank one modifications to an eigenvalue problem. For doing so, we develop fast approximations that sort the set of candidate vectors that induce the rank one modifications, without requiring solution of the modified eigenvalue problem. Based on theoretical insights into symmetric rank one eigenvalue modifications, we derive a variation of the greedy method that is faster than the standard approach and yields better results for the cases studied. The proposed approach is illustrated by numerical experiments, where we observe a speed-up by two orders of magnitude when compared to the standard greedy method while arriving at a better quality reduced model.
Keyword:
model reduction
dimensionality reduction
rank-one modifications of the symmetric eigenproblem
missing point estimation
discrete empirical interpolation
DEIM
gappy proper orthogonal decomposition
POD
masked projection
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

SIAM Journal on Scientific Computing 封面图
SIAM Journal on Scientific Computing
IF:
2.6
论文数:
5.1K
被引数:
1.8W

机构

B
Braunschweig University of Technology
学者数:
7.8K
论文数: 6.7K
被引数: 19
引用论文

引用论文

Age Differences in the Useful Field of View: An Eye Movement Analysis
err1994-12-01
err0
PREAI
errCHARLES T. SCIALFA; DAVID M. THOMAS; KENNETH M. JOFFE
err分享
err收藏
SARS Cov‐2 vaccination induces de novo donor‐specific HLA antibodies in a renal transplant patient on waiting list: A case report
errHLA
IF0
err2021-11-28
err0
errOAAI
errAhmad Abu‐Khader; Wenjie Wang; Meriam Berka; Iwona Galaszkiewicz; Faisal Khan; Noureddine Berka
err分享
err收藏
BPI22-019: Guidelines and Recommendations for the Adjuvanted Recombinant Zoster Vaccine in Immunocompromised Cancer Patients
err2022-03-31
err0
PREAI
errAnamaria Jorga; Leonard R Friedland; Nicolas Lecrenier; Ekaterina Safonova; Peter Vink; Robyn Widenmaier
err分享
err收藏
err分享
err收藏
Carbon-supported metal single atom catalysts
err2018-02-01
err0
PREAI
errHai Li; Hai-xia Zhang; Xiao-li Yan; Bing-she Xu; Jun-jie Guo
err分享
err收藏
err分享
err收藏
学者 查看更多内容