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dc.contributor.authorNoriega Angarita, Eliana Mariaspa
dc.contributor.authorSousa Santos, Vladimirspa
dc.contributor.authorQuintero Duran, Michell Josepspa
dc.contributor.authorGil Arrieta, Cesar Javierspa
dc.date.accessioned2018-11-09T19:23:36Z
dc.date.available2018-11-09T19:23:36Z
dc.date.issued2016
dc.identifier.issn23198613spa
dc.identifier.urihttp://hdl.handle.net/11323/817spa
dc.description.abstractThis paper presents a prediction model of solar radiation for dimensioning photovoltaic generation systems in the Atlantic Coast of Colombia, using artificial neural networks. As a case of study is presented the municipality "El Carmen de Bolivar" located in this region. To obtain the model, the average data of daily temperature, relative humidity and solar radiation from the last ten years, reported by weather stations in this city were used. Six neural networks were designed with six variants of input variables (temperature, humidity and month) and the output variable (solar radiation). The best result was obtained using all input variables. In the training process, the correlation index (R) between solar radiation estimated by the model and the recorded data was 0.8. In validating the correlation index was 0.77.spa
dc.language.isoeng
dc.publisherInternational Journal of Engineering and Technologyspa
dc.rightsAtribución – No comercial – Compartir igualspa
dc.subjectArtificial neural networkseng
dc.subjectModellingeng
dc.subjectPhotovoltaic generation systemseng
dc.subjectPredictioneng
dc.subjectSolar radiationeng
dc.titleSolar radiation prediction for dimensioning photovoltaic systems using artificial neural networkseng
dc.typeArtículo de revistaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
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dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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