Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2292
Título: Predicting solar radiation with RBF neural networks
Autor: Ferreira, P. M.
Ruano, A. E.
Palavras-chave: Neural Networks
Greenhouse Environmental Control
Radial Basis Functions
Solar Radiation Prediction
Time Series
Data: 2004
Citação: Ferreira, P. M.; Ruano, A. E. Predicting solar radiation with RBF neural networks. Trabalho apresentado em 6th Portuguese Conference on Automatic Control (Controlo 2004), In 6th Portuguese Conference on Automatic Control (Controlo 2004), Faro, 2004.
Resumo: In this paper radial basis function neural networks are applied to the prediction of global solar radiation. The networks are employed as one-step-ahead predictors of the solar radiation time series and iterated over time to obtain longer term predictions. Several models are compared varying the input dimension, the network size and the time series sampling rate. An empiric rule is proposed for network input selection. All networks are trained using one data set and evaluated for prediction performance on unseen data. Predictor performance is assessed taking root mean square measures of the error over the prediction horizon. The aim of this work is to select a model to be used in a climate simulator for an hydroponic greenhouse.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2292
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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