DocumentCode
1405602
Title
Evolving Gaussian RBF network for nonlinear time series modelling and prediction
Author
Aiguo, Song ; Jiren, Lu
Author_Institution
Dept. of Radio Eng., Southeast Univ., Nanjing, China
Volume
34
Issue
12
fYear
1998
fDate
6/11/1998 12:00:00 AM
Firstpage
1241
Lastpage
1243
Abstract
A genetic algorithm and recursive least squares (RLS) learning algorithm for a Gaussian radial basis function network is described, for modelling and predicting nonlinear time series. Better generalisation performance can be achieved than that of the usual clustering and RLS method
Keywords
feedforward neural nets; genetic algorithms; learning (artificial intelligence); least squares approximations; prediction theory; time series; Gaussian radial basis function network; evolution; genetic algorithm; modelling; nonlinear time series; prediction; recursive least squares learning algorithm;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19980839
Filename
702399
Link To Document