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Electric load demand prediction using neural network trained by Kalman filtering

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3 Author(s)
E. N. Sanchez ; CINVESTAV, Guadalajara, Mexico ; A. Y. Alanis ; J. Rico

This work presents the application of recurrent multilayer perceptron neural networks to electric load demand prediction; the respective training is performed extended Kalman filtering. The goal is to obtain a 24 hours horizon, prediction for the electric load demand; data from the state of California, USA, is utilized.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:4 )

Date of Conference:

25-29 July 2004