Suscripción a Biblioteca: Guest
Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones
International Journal for Uncertainty Quantification
Factor de Impacto: 3.259 Factor de Impacto de 5 años: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Imprimir: 2152-5080
ISSN En Línea: 2152-5099

Acceso abierto

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2017020027
pages 285-301

ADAPTIVE SELECTION OF SAMPLING POINTS FOR UNCERTAINTY QUANTIFICATION

Enrico Camporeale
Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands
Ashutosh Agnihotri
Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands
Casper Rutjes
Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands

SINOPSIS

We present a simple and robust strategy for the selection of sampling points in uncertainty quantification. The goal is to achieve the fastest possible convergence in the cumulative distribution function of a stochastic output of interest. We assume that the output of interest is the outcome of a computationally expensive nonlinear mapping of an input random variable, whose probability density function is known. We use a radial function basis to construct an accurate interpolant of the mapping. This strategy enables adding new sampling points one at a time, adaptively. This takes into full account the previous evaluations of the target nonlinear function. We present comparisons with a stochastic collocation method based on the Clenshaw-Curtis quadrature rule, and with an adaptive method based on hierarchical surplus, showing that the new method often results in a large computational saving.


Articles with similar content:

DIMENSIONALITY REDUCTION FOR COMPLEX MODELS VIA BAYESIAN COMPRESSIVE SENSING
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 1
Bert J. Debusschere, Habib N. Najm, Peter Thornton, Cosmin Safta, Khachik Sargsyan, Daniel Ricciuto
ADAPTIVE SAMPLING WITH TOPOLOGICAL SCORES
International Journal for Uncertainty Quantification, Vol.3, 2013, issue 2
Dan Maljovec, Valerio Pascucci, Bei Wang, Ana Kupresanin, Gardar Johannesson, Peer-Timo Bremer
A NOVEL GLOBAL METHOD FOR RELIABILITY ANALYSIS WITH KRIGING
International Journal for Uncertainty Quantification, Vol.6, 2016, issue 5
Zhengming Wang, Xiaojun Duan, Zigan Zhao
Adaptive Filtration with Constraints on Estimated Parameters
Journal of Automation and Information Sciences, Vol.38, 2006, issue 5
Elena V. Podladchikova, Nina A. Naroditskaya, Vladimir N. Podladchikov
Numerical Approach to Parametric Identification of Dynamical Systems
Journal of Automation and Information Sciences, Vol.46, 2014, issue 3
Vagif Maarif oglu Abdullayev, Kamil Rajab ogly Aida-zade