Monthly stream flow forecasting using an neural fuzzy network model

Abstract

This paper presents an fuzzy neural network model for inflow forecast for the Sobradinho hydroelectric power plant, part of the Chesf (Companhia Hidreletrica do Sao Francisco-Brazil) system. The model was implemented to forecast monthly average inflow on an one-step-ahead basis. The fuzzy neural network model is shown to provide better representation of the monthly average water inflow forecasting, than the models based on Box-Jenkins method, currently in use on the Brazilian electrical sector.