Cascade correlation networks for electricity spot price forecasting in Brasil
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.
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| Main Authors: | , |
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| Format: | Digital revista |
| Language: | spa |
| Published: |
Universidad de Ciencias Aplicadas y Ambientales U.D.C.A
2011
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| Online Access: | https://revistas.udca.edu.co/index.php/ruadc/article/view/793 |
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