International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 8, No. 5, 8 May 2016
Cover page and Table of Contents: PDF (size: 484KB)
An Ensemble of Adaptive Neuro-Fuzzy Kohonen Networks for Online Data Stream Fuzzy Clustering
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Author(s)
Zhengbing Hu
1,*
Yevgeniy V. Bodyanskiy
2
Oleksii K. Tyshchenko
2
Olena O. Boiko
2
Index Terms
Computational Intelligence, Data Stream Processing, Neuro-Fuzzy System, Fuzzy Clustering, Machine Learning
Abstract
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.
Cite This Paper
Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, Olena O. Boiko, "An Ensemble of Adaptive Neuro-Fuzzy Kohonen Networks for Online Data Stream Fuzzy Clustering", International Journal of Modern Education and Computer Science(IJMECS), Vol.8, No.5, pp.12-18, 2016. DOI:10.5815/ijmecs.2016.05.02
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