An Evolving Cascade System Based on a Set of Neo - Fuzzy Nodes

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Author(s)

Zhengbing Hu 1,* Yevgeniy V. Bodyanskiy 2 Oleksii K. Tyshchenko 2 Olena O. Boiko 2

1. School of Educational Information Technology, Central China Normal University, Wuhan, China

2. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2016.09.01

Received: 18 Feb. 2016 / Revised: 27 Jun. 2016 / Accepted: 28 Jul. 2016 / Published: 8 Sep. 2016

Index Terms

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

Abstract

Neo-fuzzy elements are used as nodes for an evolving cascade system. The proposed system can tune both its parameters and architecture in an online mode. It can be used for solving a wide range of Data Mining tasks (namely time series forecasting). The evolving cascade system with neo-fuzzy nodes can process rather large data sets with high speed and effectiveness.

Cite This Paper

Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, Olena O. Boiko, "An Evolving Cascade System Based on a Set of Neo - Fuzzy Nodes", International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.9, pp.1-7, 2016. DOI:10.5815/ijisa.2016.09.01

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