Reservoir systems operation model using simulation and neural network

Abstract

For multi-reservoir operating rules, a simulation-based neural network model is developed in this study. In the suggested model, multi-reservoir operating rules are derived using a neural network from the results of simulation. The training of the neural network is done using a supervised learning approach with the back propagation algorithm. The Yellow River upstream multi- reservoir system is used for this study. This paper presents the usefiilness of the neural network in deriving general operating policies for a multi-reservoir system. © 2005 by International Federation for Information Processing.