Identification of Dynamic systems using a Genetic Algorithm-based Fuzzy Wavelet Neural Network approach

被引：0
|
作者：
Titel, Faouzi [1 ]
Belarbi, Khaled [2 ]
机构：
[1] Univ 20 Aout 1955 Skikda, Fac Technol, Dept Genie Elect, Skikda, Algeria
[2] Univ Constantine, Fac Engn, Dept Elect, Constantine, Algeria
来源：
2013 3D INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC) | 2013年
关键词：
wavelet neural network; genetic algorithms; fuzzy inference system; fuzzy wavelet; identification; dynamic systems; DESIGN; INTERPRETABILITY; CONTROLLERS;
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 this work, a genetic algorithm based approach for designing fuzzy wavelet neural network (FWNN) is developed. The FWNN approach combines fuzzy set theory and wavelet neural networks. Thus, the proposed Fuzzy WNN is implemented through an interconnected network including two network structures, one containing the fuzzy reasoning mechanism and the other containing Wavelet neural networks. Then a simple genetic algorithm is used to find optimal values of the parameters of the both network structures. The ability of the technique FWNN in identifying non linear dynamical systems is demonstrated on two examples.
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页数：6
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