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A strategy for improving speed of the previously proposed evolving neuro-fuzzy model (ENFM) is presented in this paper to make it more appropriate for online applications. By considering a recursive extension of Gath–Geva clustering, the ENFM takes advantage of elliptical clusters for defining validity region of its neurons which leads to better modeling with less number of neurons. But this necessitates...
A novel online learning approach for neuro-fuzzy models is proposed in this paper. Unlike most of the previous online methods which use spherical clusters to define validity region of neurons, the proposed learning method is based on a recursive extension of Gath–Geva clustering algorithm, which is capable of constructing elliptical clusters as well. Eliminating the constraint of spherical clusters...
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