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Multiobjective Local Search Techniques for Evolutionary Polygonal Approximation

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorGuerrero Madrid, José Luises
dc.contributor.authorBerlanga de Jesús, Antonioes
dc.contributor.authorMolina López, José Manueles
dc.date.accessioned2015-10-08T10:25:12Z
dc.date.available2015-10-08T10:25:12Z
dc.date.issued2013
dc.descriptionProceedings of: 10th International Symposium on Distributed Computing and Artificial Intelligence . University of Salamanca (DCAI 2013). Salamanca, Spain, Spain, May 22-24, 2013.en
dc.description.abstractPolygonal approximation is based on the division of a closed curve into a set of segments. This problem has been traditionally approached as a single-objective optimization issue where the representation error was minimized according to a set of restrictions and parameters. When these approaches try to be subsumed into more recent multi-objective ones, a number of issues arise. Current work successfully adapts two of these traditional approaches and introduces them as initialization procedures for a MOEA approach to polygonal approximation, being the results, both for initial and final fronts, analyzed according to their statistical significance over a set of traditional curves from the domain.en
dc.description.sponsorshipThis work was supported in part by Projects MEyC TEC2012-37832-C02-01, MEyC TEC2011-28626-C02-02 and CAM CONTEXTS (S2009/TIC-1485).en
dc.description.statusPublicadoes
dc.format.extent8
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationOmatu, S., et al. (eds.) Distributed Computing and Artificial Intelligence: 10th International Conference. (pp. 171-178). (Advances in Intelligent Systems and Computing; 217). Springer International Publishing.en
dc.identifier.doi10.1007/978-3-319-00551-5_21
dc.identifier.isbn978-3-319-00550-8 (print)
dc.identifier.isbn978-3-319-00551-5 (online)
dc.identifier.issn2194-5357
dc.identifier.publicationfirstpage171
dc.identifier.publicationlastpage178
dc.identifier.publicationtitleDistributed Computing and Artificial Intelligence: 10th International Conferenceen
dc.identifier.urihttps://hdl.handle.net/10016/21676
dc.identifier.uxxiCC/0000021633
dc.language.isoengen
dc.publisherSpringeren
dc.relation.eventdateMay 22-24, 2013en
dc.relation.eventnumber10
dc.relation.eventplaceSalamancaes
dc.relation.eventtitle10th International Symposium on Distributed Computing and Artificial Intelligence . University of Salamanca (DCAI 2013)en
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computingen
dc.relation.ispartofseries217
dc.relation.projectIDGobierno de España. TEC2012-37832-C02-01en
dc.relation.projectIDGobierno de España. TEC2011-28626-C02-02en
dc.relation.projectIDComunidad de Madrid. S2009/TIC-1485/CONTEXTSen
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-319-00551-5_21
dc.rights© 2013 Springer International Publishing Switzerlanden
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherPolygonal approximationen
dc.subject.otherMulti-Objective Evolutionary Algorithmsen
dc.subject.otherPareto-optimal fronten
dc.subject.otherEvolutionary algorithmsen
dc.titleMultiobjective Local Search Techniques for Evolutionary Polygonal Approximationen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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