An adaptive neural fuzzy network model for seasonal stream flow forecasting

Author

Ballini, Rosangla ; Soares, Secundino ; Andrade, Marinho Gomes

Author_Institution

Dept. of Syst. Eng., Univ. Estadual de Campinas, Sao Paulo, Brazil

fYear

1998

fDate

9-11 Dec 1998

Firstpage

215

Lastpage

219

Abstract

This paper presents an adaptive neural fuzzy network model for seasonal stream flow forecasting. The model is based on a constructive learning method that adds neurons to the network structure whenever new knowledge is necessary so that it learns the fuzzy rules and membership functions essential for modeling a fuzzy system. The model was implemented to forecast monthly average inflow on an one-step-ahead basis. It was tested on three hydroelectric plants located in different river basins in Brazil. When the results were compared with those of a multilayer feedforward neural network model, the present model revealed at least a 50% decrease in the forecasting error

Keywords

forecasting theory; fuzzy neural nets; fuzzy set theory; hydroelectric power stations; learning (artificial intelligence); rivers; adaptive neural network; constructive learning; fuzzy neural nets; fuzzy set theory; hydroelectric plants; membership functions; seasonal stream flow forecasting; Adaptive systems; Fuzzy neural networks; Fuzzy systems; Learning systems; Multi-layer neural network; Neural networks; Neurons; Predictive models; Rivers; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1998. Proceedings. Vth Brazilian Symposium on

Conference_Location

Belo Horizonte

Print_ISBN

0-8186-8629-4

Type

conf

DOI

10.1109/SBRN.1998.731032

Filename

731032