Optimizing Fuzzy Flip-Flop Based Neural Networks by Bacterial Memetic Algorithm

被引：0

作者：

Lovassy, Rita ^{[1
]}

Koczy, Laszlo T. ^{[1
]}

Gal, Laszlo ^{[1
]}

机构：

[1] Szechenyi Istvan Univ Gyor, Fac Engn Sci, Szeged, Hungary

来源：

PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE | 2009年

关键词：

Bacterial Memetic Algorithm; feedbacked fuzzy J-K and fuzzy D flip-flops; Multilayer Perceptron Neural Networks;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In our previous work we proposed a Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flip-flops (F-3) based on various operations. We showed that such kind of fuzzy-neural network had good learning properties. In this paper we propose an evolutionary approach for optimizing fuzzy flip-flop networks (FNN). Various popular fuzzy operation and three different fuzzy flip-flop types will be compared from the point of view of the respective fuzzy-neural networks' approximation capability.

引用

页码：1508 / 1513

页数：6

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