Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
Revista U.D.C.A Actualidad & Divulgación Científica
versión impresa ISSN 0123-4226
Resumen
VILLA, Fernán y VELASQUEZ, Juan. CASCADE CORRELATION NETWORKS FOR ELECTRICITY SPOT PRICE FORECASTING IN BRASIL. rev.udcaactual.divulg.cient. [online]. 2011, vol.14, n.2, pp.161-167. ISSN 0123-4226.
The aim of this paper is to propose the use of regularized cascade correlation neural networks to forecast the monthly Brazilian electricity spot price. The cascade correlation models have been regularized with weight decay, weight elimination and ridge regression techniques, and several regularized models have been estimated. The results show that the regularized cascade correlation network represents the dynamic series better than other similar models such as the multilayer perceptron (MLP) and ARIMA. Then the regularized cascade correlation neural networks allow finding a suitable model to forecast the monthly Brazilian electricity spot price.
Palabras clave : Forecasting; neural networks; liberalized markets.