Abstract:
In this study an artificial neural networks (ANNs) model, multi-layer perception using back-propagation
algorithm (MLP/BP) was used for predicting flow discharge in the Balarood River which located in Khozestan
province, Iran. The rain and temperature data as monthly collected at the five meteorology stations near the
Balarood basin, and corresponding them the measured discharge at the Dokohe hydrometric station on the
Balarood river were used to train and validate the ANN model. The ANN model was performed by varying the
network parameters to minimize the prediction error and determine the optimum network configuration. The
results show that the best architecture for the MLP/BP model comprised of 10 neurons in the hidden layer and a
learning rate of 0.01. Overall, the performance of the MLP/BP neural network was good in predicting the
discharge of Balarood River. This information can be used for proper water management studies in that area.
