Variance-based sensitivity analysis for time-dependent processes
作者： Alen Alexanderian , Ralph C. Smith , Pierre A. Gremaud
DOI:
关键词: Applied mathematics 、 Computation 、 Harmonic oscillator 、 Mathematics 、 A priori and a posteriori 、 Mathematical optimization 、 Correlation 、 Variance (accounting) 、 Nonlinear system 、 Structure (category theory) 、 Variance-based sensitivity analysis
摘要: The global sensitivity analysis of time-dependent processes requires history-aware approaches. We develop for that purpose a variance-based method leverages the correlation structure problems under study and employs surrogate models to accelerate computations. errors resulting from fixing unimportant uncertain parameters their nominal values are analyzed through priori estimates. illustrate our approach on harmonic oscillator example nonlinear dynamic cholera model.
arxiv.org参考文章(43)
Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola, Global Sensitivity Analysis: The Primer ,(2008)
O. M. Knio, O. P. Le Maître, Spectral methods for uncertainty quantification : with applications to computational fluid dynamics Springer. ,(2010)
Roger G. Ghanem, Pol D. Spanos, Stochastic Finite Elements: A Spectral Approach ,(1990)
Giuseppe Da Prato, Jerzy Zabczyk, Stochastic Equations in Infinite Dimensions ,(1992)
Lloyd N. Trefethen, David Bau, Numerical Linear Algebra ,(1997)
Walter Rudin, Real and complex analysis ,(1966)
Dongbin Xiu, Numerical Methods for Stochastic Computations: A Spectral Method Approach ,(2010)
Katherine Campbell, Michael D. McKay, Brian J. Williams, Sensitivity analysis when model outputs are functions Reliability Engineering & System Safety. ,vol. 91, pp. 1468- 1472 ,(2006) , 10.1016/J.RESS.2005.11.049
Art B. Owen, Better estimation of small sobol' sensitivity indices ACM Transactions on Modeling and Computer Simulation. ,vol. 23, pp. 11- ,(2013) , 10.1145/2457459.2457460
Liang Yan, Ling Guo, Dongbin Xiu, STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁 1 -MINIMIZATION International Journal for Uncertainty Quantification. ,vol. 2, pp. 279- 293 ,(2012) , 10.1615/INT.J.UNCERTAINTYQUANTIFICATION.2012003925