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dc.contributor.authorPeri, Daniele
dc.date.accessioned2020-11-13T16:37:53Z
dc.date.available2020-11-13T16:37:53Z
dc.date.created2015
dc.date.issued2015
dc.identifier.citationPeri, D. Improving predictive quality of kriging metamodel by variogram adaptation. A: MARINE VI. "MARINE VI : proceedings of the VI International Conference on Computational Methods in Marine Engineering". CIMNE, 2015, p. 200-209. ISBN 978-84-943928-6-3.
dc.identifier.isbn978-84-943928-6-3
dc.identifier.urihttp://hdl.handle.net/2117/332193
dc.description.abstractApplication of interpolation/approximation techniques (metamodels, for brevity) is commonly adopted in numerical optimization, typically to reduce the overall execution time of the optimization process. A limited number of trial solution are computed, cov- ering the design variable space: those trial points are then used for the determination of an estimate of the objective function in any desired location of the design space. The behaviour of the prediction of the objective function in between two trial points depends on the structure of the adopted metamodel, and there is no possibility, in principle, to determine a priori if one method is preferable to another. Nevertheless, some metamodels require the adjustment of a set of tuning parameters, and this operation is critical for the prevision qualities of the metamodel. In this paper, some base parameters of the kernel of the kriging metamodel are tuned in order to improve the overall quality of the prediction.
dc.format.extent15 p.
dc.language.isoeng
dc.publisherCIMNE
dc.rightsOpen access
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits
dc.subject.lcshFinite element method
dc.subject.lcshMarine engineering
dc.subject.otherInterpolation/approximation methods, Metamodels, Kriging Interpolation
dc.titleImproving predictive quality of kriging metamodel by variogram adaptation
dc.typeConference report
dc.rights.accessOpen Access
local.citation.contributorMARINE VI
local.citation.publicationNameMARINE VI : proceedings of the VI International Conference on Computational Methods in Marine Engineering
local.citation.startingPage200
local.citation.endingPage209


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