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Prediction of the solar radiation using RBF neural networks and ground-to-sky images

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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.

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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.

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