A black-box method for parametric model order reduction

M. Geuss; B. Lohmann; B. Peherstorfer; K. Willcox

doi:10.1016/j.ifacol.2015.05.131

A black-box method for parametric model order reduction

M. Geuss, B. Lohmann, B. Peherstorfer, K. Willcox

Mathematics

Research output: Contribution to journal › Conference article › peer-review

Abstract

A black-box method for parametric model order reduction is presented that includes method selection, model refinement and error prediction using a cross-validation-based error indicator. The method is demonstrated for the interpolation of reduced system matrices.

Original language	English (US)
Pages (from-to)	168-169
Number of pages	2
Journal	IFAC-PapersOnLine
Volume	28
Issue number	1
DOIs	https://doi.org/10.1016/j.ifacol.2015.05.131
State	Published - Feb 1 2015
Event	8th Vienna International Conference on Mathematical Modelling, MATHMOD 2015 - Vienna, Austria Duration: Feb 18 2015 → Feb 20 2015

Keywords

Cross-validation
Error prediction
Matrix interpolation
Method selection
Model refinement
Parametric model order reduction
Surrogate model

ASJC Scopus subject areas

Control and Systems Engineering

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10.1016/j.ifacol.2015.05.131

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title = "A black-box method for parametric model order reduction",

abstract = "A black-box method for parametric model order reduction is presented that includes method selection, model refinement and error prediction using a cross-validation-based error indicator. The method is demonstrated for the interpolation of reduced system matrices.",

keywords = "Cross-validation, Error prediction, Matrix interpolation, Method selection, Model refinement, Parametric model order reduction, Surrogate model",

author = "M. Geuss and B. Lohmann and B. Peherstorfer and K. Willcox",

note = "Publisher Copyright: {\textcopyright} 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.; 8th Vienna International Conference on Mathematical Modelling, MATHMOD 2015 ; Conference date: 18-02-2015 Through 20-02-2015",

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AU - Geuss, M.

AU - Lohmann, B.

AU - Peherstorfer, B.

AU - Willcox, K.

PY - 2015/2/1

Y1 - 2015/2/1

N2 - A black-box method for parametric model order reduction is presented that includes method selection, model refinement and error prediction using a cross-validation-based error indicator. The method is demonstrated for the interpolation of reduced system matrices.

AB - A black-box method for parametric model order reduction is presented that includes method selection, model refinement and error prediction using a cross-validation-based error indicator. The method is demonstrated for the interpolation of reduced system matrices.

KW - Cross-validation

KW - Error prediction

KW - Matrix interpolation

KW - Method selection

KW - Model refinement

KW - Parametric model order reduction

KW - Surrogate model

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U2 - 10.1016/j.ifacol.2015.05.131

DO - 10.1016/j.ifacol.2015.05.131

M3 - Conference article

AN - SCOPUS:84954138596

SN - 2405-8963

VL - 28

SP - 168

EP - 169

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 1

T2 - 8th Vienna International Conference on Mathematical Modelling, MATHMOD 2015

Y2 - 18 February 2015 through 20 February 2015

ER -

A black-box method for parametric model order reduction

Abstract

Keywords

ASJC Scopus subject areas

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