Comparison of the performance and reliability between improved sampling strategies for polynomial chaos expansion
| Autor: | Konstantin Weise, Erik Müller, Lucas Poßner, Thomas R. Knösche |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Mathematical Biosciences and Engineering, Vol 19, Iss 8, Pp 7425-7480 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1551-0018 46597573 |
| DOI: | 10.3934/mbe.2022351?viewType=HTML |
| Popis: | As uncertainty and sensitivity analysis of complex models grows ever more important, the difficulty of their timely realizations highlights a need for more efficient numerical operations. Non-intrusive Polynomial Chaos methods are highly efficient and accurate methods of mapping input-output relationships to investigate complex models. There is substantial potential to increase the efficacy of the method regarding the selected sampling scheme. We examine state-of-the-art sampling schemes categorized in space-filling-optimal designs such as Latin Hypercube sampling and L1-optimal sampling and compare their empirical performance against standard random sampling. The analysis was performed in the context of L1 minimization using the least-angle regression algorithm to fit the GPCE regression models. Due to the random nature of the sampling schemes, we compared different sampling approaches using statistical stability measures and evaluated the success rates to construct a surrogate model with relative errors of |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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