Publication detail

Adaptive Sequential Sampling for Polynomial Chaos Expansion

NOVÁK, L. VOŘECHOVSKÝ, M. SADÍLEK, V.

Original Title

Adaptive Sequential Sampling for Polynomial Chaos Expansion

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Polynomial Chaos Expansion; Adaptive Sampling; Sequential Sampling

Authors

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

Released

28. 6. 2021

Publisher

National Technical University of Athens

Location

Athens, Greece

ISBN

978-618-85072-6-5

Book

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

Pages from

296

Pages to

301

Pages count

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"
}