Detail publikace

Adaptive Sequential Sampling for Polynomial Chaos Expansion

NOVÁK, L. VOŘECHOVSKÝ, M. SADÍLEK, V.

Originální název

Adaptive Sequential Sampling for Polynomial Chaos Expansion

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper presents a sampling strategy created specifically for surrogate modeling via polynomial chaos expansion. The proposed method combines adaptivity of surrogate model and sequential sampling enabling one-by-one extension of an experimental design. The iteration process of sequential sampling selects from a large pool of candidate points by trying to cover the design domain proportionally to their local variance contribution. The criterion for the sample selection balances between exploitation of the surrogate model and exploration of the design domain. The obtained numerical results confirm its superiority over standard non-sequential approaches in terms of surrogate model accuracy and estimation of the output variance.

Klíčová slova

Polynomial Chaos Expansion; Adaptive Sampling; Sequential Sampling

Autoři

NOVÁK, L.; VOŘECHOVSKÝ, M.; SADÍLEK, V.

Vydáno

28. 6. 2021

Nakladatel

National Technical University of Athens

Místo

Athens, Greece

ISBN

978-618-85072-6-5

Kniha

Proceedings of the 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering

Strany od

296

Strany do

301

Strany počet

6

BibTex

@inproceedings{BUT176065,
  author="Lukáš {Novák} and Miroslav {Vořechovský} and Václav {Sadílek}",
  title="Adaptive Sequential Sampling for Polynomial Chaos Expansion
",
  booktitle="Proceedings of the 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering",
  year="2021",
  pages="296--301",
  publisher="National Technical University of Athens",
  address="Athens, Greece",
  doi="10.7712/120221.8038.18955",
  isbn="978-618-85072-6-5"
}