Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2359
Título: Prediction of the solar radiation using RBF neural networks and ground-to-sky images
Autor: Crispim, E. M.
Ferreira, P. M.
Ruano, A. E.
Data: 2006
Citação: Crispim, E. M.; Ferreira, P.M.; Ruano, A. E. Prediction of the solar radiation using RBF neural networks and ground-to-sky images, Trabalho apresentado em Global Education Techology Symposium (GETS 2006), In Proceedings of the Global Education Techology Symposium (GETS 2006), Faro, 2006.
Resumo: In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2359
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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