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Metamodel variability analysis combining bootstrapping and validation techniques

Dellino, Gabriella and Meloni, Carlo Metamodel variability analysis combining bootstrapping and validation techniques. In: WSC '12 Proceedings of the Winter Simulation Conference. ACM. ISBN 978-1-4673-4780-8 (2012)

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Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of the EOQ model show encouraging results.

Item Type: Book Section
Additional Information: Article No.: 334
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Research Area: Economics and Institutional Change
Depositing User: Users 17 not found.
Date Deposited: 14 Dec 2012 08:26
Last Modified: 29 Jan 2014 13:54
URI: http://eprints.imtlucca.it/id/eprint/1444

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