THE INSTANCE SELECTION METHOD FOR NEURO-FUZZY MODEL SYNTHESIS

Authors

  • Sergey A. Subbotin

DOI:

https://doi.org/10.47839/ijc.13.3.630

Keywords:

instance, neuro-fuzzy network, sample selection, data dimensionality reduction.

Abstract

The problem of automation of neuro-fuzzy model synthesis on instance set is addressed. The method of instance selection for neuro-fuzzy model synthesis is proposed. It allows reducing the sample size, and decreasing the requirements to computer resources. The method also performs transformation of the original multi-dimensional coordinate set to the one-dimensional axis, which is also discretized to improve the data generalization properties. The software implementing proposed method is developed. The experiments were conducted to study the proposed method at the real problem solution. The results of experiments allow recommending proposed method for usage at practice.

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Published

2014-08-01

How to Cite

Subbotin, S. A. (2014). THE INSTANCE SELECTION METHOD FOR NEURO-FUZZY MODEL SYNTHESIS. International Journal of Computing, 13(3), 170-175. https://doi.org/10.47839/ijc.13.3.630

Issue

2014, Volume 13, Issue 3

Section

Articles

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