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dc.contributor.authorLoucera Muñecas, Carlos
dc.contributor.authorIglesias Prieto, Andrés 
dc.contributor.authorGálvez Tomida, Akemi 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2017-09-04T14:43:04Z
dc.date.available2017-09-04T14:43:04Z
dc.date.issued2017
dc.identifier.issn1877-0509
dc.identifier.otherTEC2013-47141-C4-Res_ES
dc.identifier.otherTIN2012-30768es_ES
dc.identifier.urihttp://hdl.handle.net/10902/11720
dc.description.abstractThis paper introduces a new memetic optimization algorithm called MeSA (Memetic Simulated Annealing) to address the data fitting problem with local-support free-form curves. The proposed method hybridizes simulated annealing with the COBYLA local search optimization method. This approach is further combined with the centripetal parameterization and the Bayesian information criterion to compute all free variables of the curve reconstruction problem with B-splines. The performance of our approach is evaluated by its application to four different shapes with local deformations and different degrees of noise and density of data points. The MeSA method has also been compared to the non-memetic version of SA. Our results show that MeSA is able to reconstruct the underlying shape of data even in the presence of noise and low density point clouds. It also outperforms SA for all the examples in this paper.es_ES
dc.description.sponsorshipThis work has been supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grants TEC2013-47141-C4-R (RACHEL) and #TIN2012-30768 (Computer Science National Program) and Toho University (Funabashi, Japan).es_ES
dc.format.extent10 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rights© 2017 The Authors. Published by Elsevier B.V.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceProcedia Computer Science, 2017, 108, 1364-1373es_ES
dc.sourceInternational Conference on Computational Science (ICCS), Zurich, Switzerland, 2017es_ES
dc.subject.otherSimulated annealinges_ES
dc.subject.otherMemetices_ES
dc.subject.otherData fittinges_ES
dc.subject.otherSplinees_ES
dc.subject.otherCOBYLAes_ES
dc.titleMemetic simulated annealing for data approximation with local-support curveses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.procs.2017.05.048es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.procs.2017.05.048
dc.type.versionpublishedVersiones_ES


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© 2017 The Authors. Published by Elsevier B.V.Excepto si se señala otra cosa, la licencia del ítem se describe como © 2017 The Authors. Published by Elsevier B.V.