Detail publikace

Monte carlo based detection of parameter correlation in simulation models

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

Originální název

Monte carlo based detection of parameter correlation in simulation models

Anglický název

Monte carlo based detection of parameter correlation in simulation models

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.

Dokumenty

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",
  annote="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.",
  address="Springer Verlag",
  booktitle="Advances in Intelligent Systems and Computing - Mechatronics 2019: Recent Advances Towards Industry 4.0",
  chapter="160010",
  doi="10.1007/978-3-030-29993-4_7",
  edition="1",
  howpublished="online",
  institution="Springer Verlag",
  year="2019",
  month="august",
  pages="54--61",
  publisher="Springer Verlag",
  type="conference paper"
}