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Prediction of the solar radiation using RBF neural networks and ground-to-sky images
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Orientador(es)
Resumo(s)
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.
Descrição
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Contexto Educativo
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.