Detail publikace

Monte carlo based detection of parameter correlation in simulation models

NAJMAN, J. BRABLC, M. RAJCHL, M. BASTL, M. SPÁČIL, T. APPEL, M.

Anglický název

Monte carlo based detection of parameter correlation in simulation models

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

en

Originální abstrakt

Simulation models which are of high order or are automatically generated via modelling software are usually depended on high number of unknown parameters. In this paper we present a method for detecting correlation between these parameters and identifying the subspace shape for their uncorrelated complements. This can be further used to lower the order of the optimization problem. For our low-order examples the methods’ operating principle is visualized and the subspace is shown.

Anglický abstrakt

Simulation models which are of high order or are automatically generated via modelling software are usually depended on high number of unknown parameters. In this paper we present a method for detecting correlation between these parameters and identifying the subspace shape for their uncorrelated complements. This can be further used to lower the order of the optimization problem. For our low-order examples the methods’ operating principle is visualized and the subspace is shown.

Klíčová slova anglicky

MATLAB;Model-Based Design;Monte Carlo;Parameter correlation;Parameter estimation;PCA;Simulation;Simulink;

Vydáno

16.08.2019

Nakladatel

Springer Verlag

Místo

Warsaw

ISBN

9783030299927

ISSN

2194-5357

Kniha

Advances in Intelligent Systems and Computing - Mechatronics 2019: Recent Advances Towards Industry 4.0

Ročník

1044

Číslo edice

1044

Strany od–do

54–61

Počet stran

8

BIBTEX


@inproceedings{BUT160010,
  author="Jan {Najman} and Martin {Brablc} and Matej {Rajchl} and Michal {Bastl} and Tomáš {Spáčil} and Martin {Appel},
  title="Monte carlo based detection of parameter correlation in simulation models",
  booktitle="Advances in Intelligent Systems and Computing - Mechatronics 2019: Recent Advances Towards Industry 4.0",
  year="2019",
  volume="1044",
  month="August",
  pages="54--61",
  publisher="Springer Verlag",
  address="Warsaw",
  isbn="9783030299927",
  issn="2194-5357"
}