Article | Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019 | Non Linear Dimension Reduction of Dynamic Model Output Linköping University Electronic Press Conference Proceedings
Göm menyn

Title:
Non Linear Dimension Reduction of Dynamic Model Output
Author:
Claire-Eleuthèriane Gerrer: Phimeca Engineering, France Sylvain Girard: Phimeca Engineering, France
DOI:
10.3384/ecp19157189
Download:
Full text (pdf)
Year:
2019
Conference:
Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019
Issue:
157
Article no.:
019
Pages:
8
No. of pages:
189-196
Publication type:
Abstract and Fulltext
Published:
2019-02-01
ISBN:
978-91-7685-122-7
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


Export in BibTex, RIS or text

Most advanced mathematical methods for the analysis of numerical model cannot cope with functional outputs of dynamic Modelica models. Principal component analysis is a well established method for dimension reduction, and can be used to tackle this issue. It relies however on a linear hypothesis that limits its applicability. We illustrate on a case study how the non linear method of autoassociative model overcomes this shortcoming and provides physically interpretable data representations.

Keywords: dimension reduction, functional data analysis, FMI, OtFMI, principal component analysis, autoassociative model, sensitivity analysis

Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019

Author:
Claire-Eleuthèriane Gerrer, Sylvain Girard
Title:
Non Linear Dimension Reduction of Dynamic Model Output
DOI:
http://dx.doi.org/10.3384/ecp19157189
References:
No references available

Proceedings of the 13th International Modelica Conference, Regensburg, Germany, March 4–6, 2019

Author:
Claire-Eleuthèriane Gerrer, Sylvain Girard
Title:
Non Linear Dimension Reduction of Dynamic Model Output
DOI:
https://doi.org10.3384/ecp19157189
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment


Responsible for this page: Peter Berkesand
Last updated: 2019-06-04