Global sensitivity analysis using a Gaussian Radial Basis Function metamodel

Zeping Wu, Donghui Wang, Patrick Okolo N, Fan Hu and Weihua Zhang

Reliability Engineering and System Safety, 2016, vol. 154, issue C, 171-179

Abstract: Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on response variables. Amongst the wide range of documented studies on sensitivity measures and analysis, Sobol' indices have received greater portion of attention due to the fact that they can provide accurate information for most models. In this paper, a novel analytical expression to compute the Sobol' indices is derived by introducing a method which uses the Gaussian Radial Basis Function to build metamodels of computationally expensive computer codes. Performance of the proposed method is validated against various analytical functions and also a structural simulation scenario. Results demonstrate that the proposed method is an efficient approach, requiring a computational cost of one to two orders of magnitude less when compared to the traditional Quasi Monte Carlo-based evaluation of Sobol' indices.

Keywords: Global sensitivity analysis; Radial Basis Function; Metamodel based sensitivity analysis; Sobol decomposition; Sobol' indices (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:154:y:2016:i:c:p:171-179

DOI: 10.1016/j.ress.2016.06.006

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