MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM

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Published: Jun 8, 2016
Keywords:
Time series, Computational intelligence, ANFIS

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Carlos Alberto Araújo Júnior
Universidade Federal de Viçosa - Viçosa, Minas Gerais, Brasil
Liniker Fernandes da Silva
Universidade Federal de Viçosa - Viçosa, Minas Gerais, Brasil
Helio Garcia Leite
Universidade Federal de Viçosa - Viçosa, Minas Gerais, Brasil
Erlon Barbosa Valdetaro
Universidade Federal de Viçosa - Viçosa, Minas Gerais, Brasil
Danilo Barros Donato
Renato Vinícius Oliveira Castro Castro
Universidade Federal de São João del Rei - São João Del Rei, Minas Gerais, Brasil

Abstract

Using a monthly time series of charcoal prices in Minas Gerais from January 2000 to September 2014, this study aimed to evaluate the use of neuro-fuzzy system to model the series and forecasting prices. We used four modeling structures for different prices lags (1, 2, 3, 4 and 5 lags). The structure most appropriate for neuro-fuzzy system was chosen based on the root mean square error, mean absolute error, mean squared error, mean absolute percentage error and maximum absolute percentage error for the forecasted period. With the results found, it is possible to conclude that a neuro-fuzzy system can be used properly to predict the charcoal prices.

Article Details

Issue
Vol. 22 No. 2 (2016)
Section
Article

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