Title :
Recurrent neural network applied in dynamitic process identification based on RPROP and chaos optimization coupling algorithm
Author :
Jiao, Song-ming ; Han, Pu ; Zhou, Li-hui ; Li, Jian-Bo
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Baoding, China
Abstract :
A new style of dynamic recurrent neural network based on RPROP and chaos optimization coupling algorithm is provided and is applied to dynamic process identification in this paper. RPROP algorithm is good at improving neural network´s convergence speed and chaos optimization algorithm can prevent efficiently from partial minimum. Moreover, a new kind of object function is applied to this network to improve the generalization capability of neural network. By the simulation experiment, the feasibility of this method was demonstrated.
Keywords :
chaos; optimisation; recurrent neural nets; RPROP; chaos optimization coupling algorithm; dynamic process identification; object function; recurrent neural network; Automation; Chaos; Convergence; Electronic mail; Feedforward neural networks; Feeds; Intelligent networks; Neural networks; Neurons; Recurrent neural networks;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1380355