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Fuzzy Inference Based Autoregressors for Time Series Prediction Using Nonparametric Residual Variance Estimation
Federico Montesino Pouzols, Amaury Lendasse and Angel Barriga Barros
In: 17th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2008), IEEE World Congress on Computational Intelligence, June 2008, Hong Kong.
AbstractA new software tool for time series prediction by
means of fuzzy inference systems is reported. This tool, named
xftsp, implements a novel methodology for time series prediction
based on methods for automatic fuzzy systems identification
and supervised learning combined with statistical methods for
nonparametric residual variance estimation. xftsp is designed
as a tool integrated in the Xfuzzy development environment
for fuzzy systems. Experiments carried out on a number of
time series benchmarks show the advantages of xftsp in terms
of both accuracy and computational requirements as compared
against Least-Squared Support Vector Machines, an established
technique in the field of time series prediction. [Edit]
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