A carregar...
Publicação
Prediction of the solar radiation evolution using computational intelligence techniques and cloudiness indices
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 82.53 KB | Adobe PDF |
Orientador(es)
Resumo(s)
In this paper, Artificial Neural Networks are applied for multi-step long term solar radiation prediction. The input-output structure of the neural network models
is selected using evolutionary computation methods. The networks are trained as onestep-
ahead predictors and iterated over time to obtain multi-step longer term predictions.
Auto-regressive and auto-regressive with exogenous inputs models are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images, captured by a CCD camera.
Descrição
Palavras-chave
Cloudiness indices Solar radiation Neural networks Multi-objective genetic algorithms
Contexto Educativo
Citação
Ruano, Antonio Eduardo de Barros; Crispim, E. M.; Ferreira, P. M. Prediction of the solar radiation evolution using computational intelligence techniques and cloudiness indices, International Journal of Innovative Computing Information and Control, 4, 5, 1121-1133, 2008.