Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization

In many real-world problems involving pattern recognition, system identification and modeling, control, decision making, and forecasting of time-series, available data are quite often of uncertain nature. An interesting alternative is to employ type-2 fuzzy sets, which augment fuzzy models with expr...

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Veröffentlicht in:	Information sciences 2011-05, Vol.181 (9), p.1591-1608
Hauptverfasser:	Aliev, Rafik A., Pedrycz, Witold, Guirimov, Babek G., Aliev, Rashad R., Ilhan, Umit, Babagil, Mustafa, Mammadli, Sadik
Format:	Artikel
Sprache:	eng
Schlagworte:	Clustering Differential evolution optimization Evolution Fuzzy Fuzzy clustering Fuzzy logic Fuzzy set theory Mathematical models Neural networks Optimization Type-2 fuzzy neural network Type-2 fuzzy rule base
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