masterThesis
Desarrollo 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 colombianas
Fecha
2012Registro en:
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TE06209
Autor
Gaitán Ospina, Carlos Felipe
Agudelo Otálora, Luis Mauricio
Institución
Resumen
Se 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/10818/9321