Sequential kernel fuzzy clustering of big data based on computational intelligence hybrid system
Journal Title: Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì - Year 2017, Vol 872, Issue
Abstract
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.
Authors and Affiliations
Yevgeniy Bodyanskiy, Anastasiia Deineko, Polina Zhernova, Oleh Zolotukhin, Yana Khaustova
Keywords
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