EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING

Authors

  • A. O. Deyneko Kharkiv National University of Radio Electronics, Ukraine
  • I. P. Pliss Kharkiv National University of Radio Electronics, Ukraine
  • Y. V. Bodiansky Kharkiv National University of Radio Electronics, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2012-1-17

Keywords:

evolving neuro-fuzzy system, normalized radialbasis function neural network, general regression neuro-fuzzy network, fuzzy support vector machine, kernel activation function.

Abstract

In this work the evolving neuro-fuzzy system with kernel activation function that contains fuzzy support vector machine, normalized radial basis function neural network and general regression neuro-fuzzy network as subsystems is proposed. This network is tuned using both optimization and memory based approaches and does not inclined to the «curse of dimensionality», is able to real time mode information processing by adapting its parameters and structure to problem conditions.

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Published

2012-07-10

How to Cite

Deyneko, A. O., Pliss, I. P., & Bodiansky, Y. V. (2012). EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING. Radio Electronics, Computer Science, Control, (1). https://doi.org/10.15588/1607-3274-2012-1-17

Issue

No. 1 (2012): Radio Electronics, Computer Science, Control

Section

Neuroinformatics and intelligent systems

License

Copyright (c) 2014 A. O. Deyneko, I. P. Pliss, Y. V. Bodiansky

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