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dc.contributor.authorSalazar-Vasquez, Fredy A.spa
dc.contributor.authorOsorio-Serna, Carlosspa
dc.contributor.authorCaicedo-Giraldo, María Alejandraspa
dc.contributor.authorAlfonso-Morales, Wilfredospa
dc.contributor.authorCaicedo-Bravo, Eduardo F.spa
dc.date.accessioned2017-07-16 00:00:00
dc.date.accessioned2022-06-13T17:42:31Z
dc.date.available2017-07-16 00:00:00
dc.date.available2022-06-13T17:42:31Z
dc.date.issued2017-07-16
dc.identifier.issn0121-3709
dc.identifier.urihttps://repositorio.unillanos.edu.co/handle/001/2725
dc.description.abstractLa metodología de clustering fue utilizada para agrupar tres barrios en Quibdó teniendo en cuenta factores que favorecen el desarrollo de la malaria. Los mapas auto-organizados de Kohonen fueron utilizados para el análisis de las características más significativas en la clasificación. Los clusters detectados fueron comparados con la clasificación geográfica de las casas, encontrando, que los mapas auto-organizados de Kohonen clasifican las casas por las condiciones ambientales propicias para el desarrollo del mosquito más que por la clasificación administrativa de la ciudad.spa
dc.description.abstractClustering methodology was used to group three neighborhoods in Quibdo taking into account factors that favor the development of malaria. The Kohonen self-organizing maps were used for the analysis of the most significant features in the standings. The detected clusters were compared with the geographical classification of houses, finding that the Kohonen self-organizing maps households classified by environmental conditions conducive to development rather than the administrative classification of the city.eng
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.publisherUniversidad de los Llanosspa
dc.rightsOrinoquia - 2019spa
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.sourcehttps://orinoquia.unillanos.edu.co/index.php/orinoquia/article/view/547spa
dc.subjectFluvialeng
dc.subjectGeomorphologyeng
dc.subjectManningeng
dc.subjectSedimentseng
dc.subjectOrotoy.eng
dc.subjectEngineeringeng
dc.subjectFluvialspa
dc.subjectGeomorfologíaspa
dc.subjectManningspa
dc.subjectSedimentosspa
dc.subjectOrotoy.spa
dc.subjectIngenieríaspa
dc.titleIdentificación de la delimitación administrativa de la malaria usando redes neuronales artificialesspa
dc.typeArtículo de revistaspa
dc.typeJournal Articleeng
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.localSección Artículosspa
dc.type.localSección Articleseng
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doi10.22579/20112629.547
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dc.relation.referencesS. F. Baracho, V. V. d. Melo and R. C. Coelho, “Automated Left Ventricle Posterior Wall Segmentation Using Kohonen Self-Organizing Map,” 2016 5th Brazilian Conference on Intelligent Systems (BRACIS), Recife, 2016, pp. 456-461.spa
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dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.identifier.eissn2011-2629
dc.identifier.urlhttps://doi.org/10.22579/20112629.547
dc.relation.bitstreamhttps://orinoquia.unillanos.edu.co/index.php/orinoquia/article/download/547/1111
dc.relation.citationeditionNúm. 1 Sup , Año 2017spa
dc.relation.citationendpage19
dc.relation.citationissue1 Supspa
dc.relation.citationstartpage11
dc.relation.citationvolume21spa
dc.relation.ispartofjournalOrinoquiaspa
dc.title.translatedBoundary Delimitiation of Malaria using Artificial Neural Networkseng
dc.type.contentTextspa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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