An Ensemble of Adaptive Neuro-Fuzzy Kohonen Networks for Online Data Stream Fuzzy Clustering

Автор: Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, Olena O. Boiko

Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs

Статья в выпуске: 5 vol.8, 2016 года.

Бесплатный доступ

A new approach to data stream clustering with the help of an ensemble of adaptive neuro-fuzzy systems is proposed. The proposed ensemble is formed with adaptive neuro-fuzzy self-organizing Kohonen maps in a parallel processing mode. Their learning procedure is carried out with different parameters that define a nature of cluster borders' blurriness. Clusters' quality is estimated in an online mode with the help of a modified partition coefficient which is calculated in a recurrent form. A final result is chosen by the best neuro-fuzzy self-organizing Kohonen map.

Computational Intelligence, Data Stream Processing, Neuro-Fuzzy System, Fuzzy Clustering, Machine Learning

Короткий адрес: https://sciup.org/15014862

IDR: 15014862

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