Flow estimation using an Elman networks

This paper investigates the application of partially recurrent artificial neural networks (ANN) in the flow estimation for Sao Francisco river that feeds the hydroelectric power plant of Sobradinho. An Elman neural network was used, suitably arranged to receive samples of the flow time series data available for Sao Francisco river shifted by one month. The data used in the application concern to the measured Sao Francisco river flow time series from 1931 to 1996, in a total of 65 years from what 60 were used for training and 5 for testing. The obtained results indicate that the Elman neural network is suitable to estimate the river flow for 5 year periods monthly. The average estimation error was less than 0.2%.