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dc.contributor.advisorGaitán Ospina, Carlos Felipe
dc.contributor.advisorAgudelo Otálora, Luis Mauricio
dc.contributor.authorCardozo Vásquez, Andrés
dc.date.accessioned2013-12-16T14:14:08Z
dc.date.available2013-12-16T14:14:08Z
dc.date.created2013-12-162
dc.date.issued2012
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dc.identifier.urihttp://hdl.handle.net/10818/9320
dc.description181 páginas
dc.description.abstractSe desarrolló un modelo basado en redes neuronales artificiales (RNA) para el pronóstico de la temperatura media diaria a escala local en 5 zonas climáticas de Colombia. Se probaron perceptrones multicapa (MLP), redes recurrentes (RN), Generalized Feedforward (GFF), Time Lagged Recurrent Networks (TLRN), Time Delayed Neural Networks (TDNN) y Radial Basis Function (RBF). Se encontraron modelos RNA que superaron métodos lineales y que simularon mejor los datos de anomalías de la temperatura media diaria que el reanálisis NCEP/NCAR. Posteriormente se hizo una proyección de la temperatura media diaria en el periodo del 1 de enero de 2001 al 31 de diciembre de 2100 bajo los escenarios A2 y A1B descritos por el Panel Intergubernamental sobre el Cambio Climático. Nota: Para consultar la carta de autorización de publicación de este documento por favor copie y pegue el siguiente enlace en su navegador de internet: http://hdl.handle.net/10818/9321es_CO
dc.language.isospaes_CO
dc.publisherUniversidad de La Sabana
dc.sourceUniversidad de La Sabana
dc.sourceIntellectum Repositorio Universidad de La Sabana
dc.subjectZonas climáticas -- Colombia
dc.subjectClima -- Colombia
dc.subjectClimatología -- Colombia
dc.titleDesarrollo de un modelo de red neuronal artificial para la reducción de escala (downscaling) de datos de temperatura del modelo Climático Global Canadiense 3.1 a estaciones meteorológicas colombianases_CO
dc.typemasterThesis
dc.publisher.programMaestría en Diseño y Gestión de Procesos
dc.publisher.departmentFacultad de Ingeniería
dc.identifier.local256456
dc.identifier.localTE06209
dc.type.localTesis de maestría
dc.type.hasVersionpublishedVersion
dc.rights.accessRightsopenAccess
dc.creator.degreeMagíster en Diseño y Gestión de Procesos


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