A new training algorithm for RBF Neural Network

被引：0

作者：

Liu, Y ^{[1
]}

Liu, BK ^{[1
]}

Li, GQ ^{[1
]}

机构：

[1] Tianjin Univ, Tianjin 300072, Peoples R China

来源：

PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年

关键词：

RBFNN (Radial Basis Function Neural Network); hybrid hierarchy genetic algorithms; Chaos time series;

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 paper, based on the study of RBFNN (Radial Basis Function Neural Network) training algorithm and genetic algorithm, a new RBF NN training algorithm -hybrid hierarchy genetic algorithm is introduced by combing hierarchy genetic algorithm and least square method. The hybrid algorithm greatly increases the training speed while is still able to determine the structure and parameter of an RBF from sample data The new training algorithm is used to identify and predict M-G chaos time series, and the simulation gives satisfied result.

引用

页码：805 / 808

页数：4

共 9 条

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