Publications
Detailed Information
Global sensitivity analysis in high dimensions with partial least squares-driven PCEs
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ehre, Max | - |
dc.contributor.author | Papaioannou, Iason | - |
dc.contributor.author | Straub, Daniel | - |
dc.date.accessioned | 2019-05-14T03:06:52Z | - |
dc.date.available | 2019-05-14T03:06:52Z | - |
dc.date.issued | 2019-05-26 | - |
dc.identifier.citation | 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019 | - |
dc.identifier.isbn | 979-11-967125-0-1 | - |
dc.identifier.other | ICASP13-291 | - |
dc.identifier.uri | https://hdl.handle.net/10371/153451 | - |
dc.description.abstract | We develop an efficient method for the computation of variance-based sensitivity indices using a recently introduced latent-variable-based polynomial chaos expansion, which is particularly suitable for high dimensional problems. By back-transforming the surrogate from its latent variable space-basis to the original input variable space-basis, we derive analytical expressions for these sensitivities that only depend on the model coefficients. Thus, once the surrogate model is built, the variance-based sensitivities can be computed at negligible computational cost as no additional sampling is required. The accuracy of the method is demonstrated with a numerical experiment of an elastic truss. | - |
dc.description.sponsorship | This project was supported by the German Research Foundation (DFG) through Grant STR 1140/6-1 under SPP 1886. | - |
dc.language.iso | en | - |
dc.title | Global sensitivity analysis in high dimensions with partial least squares-driven PCEs | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.22725/ICASP13.291 | - |
dc.sortNo | 709 | - |
dc.citation.pages | 1537-1544 | - |
- Appears in Collections:
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.