Sequential kernel fuzzy clustering of big data based on computational intelligence hybrid system

Authors:

Yevgeniy Bodyanskiy, Anastasiia Deineko, Polina Zhernova , Oleh Zolotukhin, Yana Khaustova

Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, 14, Nauky av. Kharkiv, 61166, Ukraine

The architecture and self-learning method of hybrid neuro-fuzzy systems for big fuzzy clustering in on-line mode are proposed in this paper. The architecture of proposed system represents the hybrid of the fuzzy general regression neural network and clustering self-organizing network. During a learning procedure in on-line mode, the proposed system tunes both its parameters and its architecture. For tuning of membership functions parameters of neuro-fuzzy system the method based on competitive learning is proposed. The hybrid neuro-fuzzy system tunes its synaptic weights, centers and width parameters of membership functions.

self-learning method of hybrid neuro-fuzzy systems

Big data

fuzzy clustering

clustering self-organizing network

fuzzy general regression neural network

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