Title :
A new training algorithm for RBF neural network
Author :
Yong, Liu ; Baokun, Liu ; Guangquan, Li
Author_Institution :
Tianjin Univ., China
Abstract :
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, the hybrid hierarchy genetic algorithm, is introduced by combining 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
Keywords :
genetic algorithms; learning (artificial intelligence); least squares approximations; radial basis function networks; GA; M-G chaos time series identification; M-G chaos time series prediction; RBF neural network; RBFNN; hybrid hierarchy genetic algorithm; least-square method; radial basis function neural network; training algorithm; Chaos; Genetic algorithms; Least squares methods; Neural networks; Predictive models; Radial basis function networks;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863340
