 Combining screening and metamodel-based methods: An efficient sequential approach for the sensitivity analysis of model outputsQiao Ge, Biagio Ciuffo and Monica Menendez Reliability Engineering and System Safety, 2015, vol. 134, issue C, 334-344 Abstract: Sensitivity analysis (SA) is able to identify the most influential parameters of a given model. Application of SA is usually critical for reducing the complexity in the subsequent model calibration and use. Unfortunately it is hardly applied, especially when the model is in the form of a computationally expensive black-box computer program. A possible solution concerns applying SA to the metamodel (i.e., an approximation of the computationally expensive model) instead. Among the other options, the use of Gaussian process metamodels (also known as Kriging metamodels) has been recently proposed for the SA of computationally expensive traffic simulation models. However, the main limitation of this approach is its dependence on the model dimensionality. When the model is high-dimensional, the estimation of the Kriging metamodel may still be problematic due to its high computational cost. Keywords: Sensitivity analysis; Variance-based approach; High-dimensional and computationally expensive model; Screening; Metamodel (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:134:y:2015:i:c:p:334-344 DOI: 10.1016/j.ress.2014.08.009 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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