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Research Project
Classification and clustering of fuzzy rules
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Publications
Time series prediction by perturbed fuzzy model
Publication . Salgado, Paulo; Gouveia, Fernando; Igrejas, Getúlio
This paper presents a fuzzy system
approach to the prediction of nonlinear
time series and dynamical systems based
on a fuzzy model that includes its
derivative information. The underlying
mechanism governing the time series,
expressed as a set of IF–THEN rules, is
discovered by a modified structure of fuzzy
system in order to capture the temporal
series and its temporal derivative information.
The task of predicting the future is
carried out by a fuzzy predictor on the
basis of the extracted rules and by the
Taylor ODE solver method. We have
applied the approach to the benchmark
Mackey-Glass chaotic time series.
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Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
POSC
Funding Award Number
POSI/SRI/41975/2001