Identification and Prediction of Nonlinear Dynamical Plants Using TSK and Wavelet Neuro-Fuzzy Models

The problem of identification consists of setting up a suitably parameterized identification model and adjusting the parameters of the model by optimizing a performance index. Parallel and parallel-series identification methods are used to adjust an unknown model's parameters. In this paper a c...

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Bibliographische Detailangaben
Hauptverfasser:	Banakar, A., Azeem, M.F.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Feedforward neural networks Fuzzy systems Heuristic algorithms Intelligent systems Mathematical model Neural networks Parallel and Series-Parallel identification model Power system modeling Predictive models Time frequency analysis TSK fuzzy model Uncertainty Wavelet Neuro-Fuzzy model
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Beschreibung
Zusammenfassung:	The problem of identification consists of setting up a suitably parameterized identification model and adjusting the parameters of the model by optimizing a performance index. Parallel and parallel-series identification methods are used to adjust an unknown model's parameters. In this paper a combined parallel/series-parallel identification model, based on TSK fuzzy model and wavelet neuro-fuzzy model, is proposed
ISSN:	1541-1672 1941-1294
DOI:	10.1109/IS.2006.348490