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Global sensitivity analysis in high dimensions with partial least squares-driven PCEs

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dc.contributor.authorEhre, Max-
dc.contributor.authorPapaioannou, Iason-
dc.contributor.authorStraub, Daniel-
dc.date.accessioned2019-05-14T03:06:52Z-
dc.date.available2019-05-14T03:06:52Z-
dc.date.issued2019-05-26-
dc.identifier.citation13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019-
dc.identifier.isbn979-11-967125-0-1-
dc.identifier.otherICASP13-291-
dc.identifier.urihttps://hdl.handle.net/10371/153451-
dc.description.abstractWe 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.sponsorshipThis project was supported by the German Research Foundation (DFG) through Grant STR 1140/6-1 under SPP 1886.-
dc.language.isoen-
dc.titleGlobal sensitivity analysis in high dimensions with partial least squares-driven PCEs-
dc.typeConference Paper-
dc.identifier.doi10.22725/ICASP13.291-
dc.sortNo709-
dc.citation.pages1537-1544-
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Civil & Environmental Engineering (건설환경공학부)ICASP13
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