Artículos de revistas
Electrical load forecasting formulation by a fast neural network
Fecha
2003-03-01Registro en:
Engineering Intelligent Systems For Electrical Engineering and Communications. Market Harboroug: C R L Publishing Ltd, v. 11, n. 1, p. 51-57, 2003.
0969-1170
WOS:000183124000006
7166279400544764
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.