The neuro-fuzzy network synthesis and simplification on precedents in problems of diagnosis and pattern recognition

被引：0

作者：

Subbotin S. ^{[1
]}

机构：

[1] Zaporizhzhya National Technical University, Zaporizhzhya

来源：

Optical Memory and Neural Networks (Information Optics) | 2013年 / 22卷 / 02期

关键词：

feature significance; feature space fuzzy partition; fuzzy production rule; fuzzy term; model synthesis; neuro-fuzzy network; simplification; training;

D O I：

10.3103/S1060992X13020082

中图分类号：

学科分类号：

摘要：

The problem of increasing of the quality, of the automation level and the synthesis rate of neuro-fuzzy network (NFN) has been solved in the paper. The method of neuro-fuzzy network synthesis and simplification on precedents has been firstly proposed. It is based on the using of the feature space pseudo-clustering, on the automatic formation of fuzzy terms and rules, on the automatic NFN structure and parameter synthesis by the training set, and on the reducing of NFN structural and parametric complexity by simplifying the rules and reducing the number of redundant terms. This can increase the speed of NFN construction, enhance its properties and generalize interpretability. The proposed method has been implemented in the developed software and was used for the practical problem solving of technical diagnosis. © 2013 Allerton Press, Inc.

引用

页码：97 / 103

页数：6

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