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Adaptive empirical distributions in the framework of inverse problems

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dc.contributor.authorSilva, Tiago
dc.contributor.authorLoja, Amélia
dc.contributor.authorCarvalho, Alda
dc.contributor.authorMaia, Nuno. M.
dc.contributor.authorBarbosa, Joaquim
dc.date.accessioned2018-02-20T09:43:48Z
dc.date.available2018-02-20T09:43:48Z
dc.date.issued2017
dc.description.abstractThis article presents an innovative framework regarding an inverse problem. One presents the extension of a global optimization algorithm to estimate not only an optimal set of modeling parameters, but also their optimal distributions. Regarding its characteristics, differential evolution algorithm is used to demonstrate this extension, although other population-based algorithms may be considered. The adaptive empirical distributions algorithm is here introduced for the same purpose. Both schemes rely on the minimization of the dissimilarity between the empirical cumulative distribution functions of two data sets, using a goodness-of-fit test to evaluate their resemblance.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSILVA, Tiago A. N.; [et al] – Adaptive empirical distributions in the framework of inverse problems. International Journal for Computational Methods in Engineering Science & Mechanics. ISSN 1550-2287. Vol. 18, N.º 6 (2017), pp. 277-291pt_PT
dc.identifier.doi10.1080/15502287.2017.1287227pt_PT
dc.identifier.issn1550-2287
dc.identifier.issn1550-2295
dc.identifier.urihttp://hdl.handle.net/10400.21/8068
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relationFCT - IDMEC - LAETA UID/EMS/50022/2013pt_PT
dc.relationFCT - IDMEC - CEM APREpt_PT
dc.relation.publisherversionhttp://www.tandfonline.com/doi/pdf/10.1080/15502287.2017.1287227?needAccess=truept_PT
dc.subjectAdaptive empirical distributionspt_PT
dc.subjectDifferential evolutionpt_PT
dc.subjectEmpirical CDFpt_PT
dc.subjectInverse problempt_PT
dc.subjectInverse samplingpt_PT
dc.subjectTwo samples Kolmogorov-Smirnov goodness-of-fit testpt_PT
dc.titleAdaptive empirical distributions in the framework of inverse problemspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FMulti%2F00491%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/PEst-OE%2FEME%2FUI0667%2F2014/PT
oaire.citation.endPage291pt_PT
oaire.citation.issue6pt_PT
oaire.citation.startPage277pt_PT
oaire.citation.titleInternational Journal for Computational Methods in Engineering Science and Mechanicspt_PT
oaire.citation.volume18pt_PT
oaire.fundingStream5876
oaire.fundingStream5876
person.familyNameSilva
person.familyNameLoja
person.familyNameCarvalho
person.familyNameBarbosa
person.givenNameTiago
person.givenNameAmélia
person.givenNameAlda
person.givenNameJoaquim
person.identifier535461
person.identifier.ciencia-idC913-F477-51D4
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person.identifier.ciencia-idFD18-CBDD-B7C7
person.identifier.ciencia-id361B-9965-016F
person.identifier.orcid0000-0002-5065-7938
person.identifier.orcid0000-0002-4452-5840
person.identifier.orcid0000-0003-2642-4947
person.identifier.orcid0000-0002-8219-6435
person.identifier.ridD-1671-2009
person.identifier.ridI-7513-2015
person.identifier.ridL-5730-2013
person.identifier.scopus-author-id26657651100
person.identifier.scopus-author-id15741348500
person.identifier.scopus-author-id25027091800
person.identifier.scopus-author-id7202435183
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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