Electric load demand prediction using neural network trained by Kalman filtering

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.