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A global optimization approach based on adaptive populations

2015-03Conference object Restricted access
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dc.contributor.authorSilva, Tiago A. N.
dc.contributor.authorLoja, Amélia
dc.contributor.authorCarvalho, Alda
dc.contributor.authorMaia, Nuno M. M.
dc.contributor.authorBarbosa, Joaquim
dc.date.accessioned2018-03-05T11:21:34Z
dc.date.available2018-03-05T11:21:34Z
dc.date.issued2015-03
dc.description.abstractThe solution of inverse problems based on experimental data is itself an important research issue. In this context and assuming that an experimental sample is available, rather than trying to find a specific deterministic solution for the inverse problem, one aims to determine the probabilistic distribution of the modelling parameters, based on the minimization of the dissimilarity between the empirical cumulative distribution function of an experimental solution and its simulation counterpart. The present paper presents na innovative framework, where Differential Evolution is extended in order to estimate not only an optimal set of modelling parameters, but to estimate their optimal probabilistic distributions. Additionally, the Adaptive Empirical Distributions optimization scheme is here introduced. Both schemes rely on the two samples Kolmogorov-Smirnov goodness-offit test in order to evaluate the resemblance between two empirical cumulative distribution functions. A numerical example is considered in order to assess the performance of the proposed strategies and validity of their solutions.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSILVA, Tiago A. N.; [et al]. – A global optimization approach based on adaptive populations. In SYMCOMP 2015. Faro, Portugal: ECCOMAS, 2015. ISBN 978-989-96264-6-1. Pp. 389-401.pt_PT
dc.identifier.isbn978-989-96264-6-1
dc.identifier.isbn978-989-96264-7-8
dc.identifier.urihttp://hdl.handle.net/10400.21/8195
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherECCOMASpt_PT
dc.relationFCT - PEst/OE/EME/LA0022/2011pt_PT
dc.relationFCT - PTDC/ATPAQI/5355/2012pt_PT
dc.subjectInverse problempt_PT
dc.subjectExtended differential evolutionpt_PT
dc.subjectAdaptive empirical distributionspt_PT
dc.titleA global optimization approach based on adaptive populationspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F44696%2F2008/PT
oaire.citation.conferencePlaceFaro, Portugal - 26-27 March 2015pt_PT
oaire.citation.endPage401pt_PT
oaire.citation.startPage389pt_PT
oaire.citation.titleSYMCOMP 2015 - 2nd International Conference on Numerical and Symbolic Computation: Advances and Applicationspt_PT
oaire.fundingStreamSFRH
person.familyNameLoja
person.familyNameCarvalho
person.familyNameBarbosa
person.givenNameAmélia
person.givenNameAlda
person.givenNameJoaquim
person.identifier535461
person.identifier.ciencia-idA016-59D1-2D00
person.identifier.ciencia-idFD18-CBDD-B7C7
person.identifier.ciencia-id361B-9965-016F
person.identifier.orcid0000-0002-4452-5840
person.identifier.orcid0000-0003-2642-4947
person.identifier.orcid0000-0002-8219-6435
person.identifier.ridI-7513-2015
person.identifier.ridL-5730-2013
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.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication9f43a546-1632-49c5-bd44-94aac2d7b648
relation.isAuthorOfPublication214fa21c-bca0-4769-99b0-5f1239d2ea41
relation.isAuthorOfPublicationa7598fac-8160-4003-ab71-5d28a11711dc
relation.isAuthorOfPublication.latestForDiscoverya7598fac-8160-4003-ab71-5d28a11711dc
relation.isProjectOfPublication4748201c-455b-4adf-89f0-c39e8722ef92
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