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  5. Recurrent fuzzy clusterization algorithm in the neuro-neo-fuzzy counterpropagation network

Recurrent fuzzy clusterization algorithm in the neuro-neo-fuzzy counterpropagation network

O.K. Tyshchenko, I.P. Pliss
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Description: The architecture that consists of neo-fuzzy-neurons and a layer of recurrent fuzzy clusterization is proposed. The proposed architecture can be used for unstationary time series forecasting.


Keywords: unclear кластеризация, neo-fuzzy-neurons , teaching algorithm, unstationary temporal rows

Reference:
 Tyshchenko, A.K. and Plyss, Y.P. (2012), “Rekurrentnыi alhorytm nechetkoi klasteryzatsyy v neiro-neo-fazzy sety vstrechnoho rasprostranenyia”, Scientific Works of Kharkiv National Air Force University, Vol. 3(32), pp. 126-129.