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An evolving connectionist system for data stream fuzzy clustering and its online learning.

Authors :
Bodyanskiy, Yevgeniy V.
Tyshchenko, Oleksii K.
Kopaliani, Daria S.
Source :
Neurocomputing. Nov2017, Vol. 262, p41-56. 16p.
Publication Year :
2017

Abstract

An evolving cascade neuro-fuzzy system and its online learning procedure are considered in this paper. The system is based on conventional Kohonen neurons. The proposed system solves a clustering task of non-stationary data streams under uncertainty conditions when data come in the form of a sequential stream in an online mode. A quality estimation process is defined by finding an optimal value of the used cluster validity index. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09252312
Volume :
262
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
124248589
Full Text :
https://doi.org/10.1016/j.neucom.2017.03.081