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NOVÁK, L. SHIELDS, M. SADÍLEK, V. VOŘECHOVSKÝ, M.
Original Title
LOCALIZED APPROXIMATIONS BY POLYNOMIAL CHAOS EXPANSIONS FOR HIGHLY NON-LINEAR FUNCTIONS
Type
conference paper
Language
English
Original Abstract
The paper presents a strategy for adaptive sequential decomposition of the design domain and for localized surrogate modeling via polynomial chaos expansion. The proposed method combines adaptivity of localized surrogate modeling and sequential sampling. The iteration process of the decomposition and sequential sampling balances between exploitation of the surrogate model and exploration of the design domain. The proposed methodology is especially beneficial for highly non-linear functions, which are extremely challenging for and approximation by polynomial chaos expansion. The obtained numerical results confirm its superiority over a single global surrogate model and a recently proposed technique based on similar concepts.
Keywords
Adaptive Sampling; Polynomial Chaos Expansion; Sequential Sampling
Authors
NOVÁK, L.; SHIELDS, M.; SADÍLEK, V.; VOŘECHOVSKÝ, M.
Released
12. 6. 2023
Publisher
National Technical University of Athens
Location
Athens, Greece
ISBN
9786185827021
Book
UNCECOMP 2023 Proceedings
Pages from
158
Pages to
164
Pages count
7
BibTex
@inproceedings{BUT187085, author="Lukáš {Novák} and Michael {Shields} and Václav {Sadílek} and Miroslav {Vořechovský}", title="LOCALIZED APPROXIMATIONS BY POLYNOMIAL CHAOS EXPANSIONS FOR HIGHLY NON-LINEAR FUNCTIONS", booktitle="UNCECOMP 2023 Proceedings", year="2023", pages="158--164", publisher="National Technical University of Athens", address="Athens, Greece", isbn="9786185827021" }