NEURAL NETWORK BASED WATER INFLOW FORECASTING

摘要

Water inflow forecasting is usually based on precipitation data collected by the ombrometer stations in the river basin. Solution of this problem is rather complex due to highly non-linear relation between the amount of precipitation at different locations and water inflow. In the paper, a new approach to forecasting water inflow into the head hydro power plant reservoir based on neural networks is described. First, selection of input parameters is discussed. Next, the most appropriate architecture of the neural network is chosen. Finally, efficacy of the proposed method is tested for a practical case and some results are presented.