Title :
Modeling for a complicated industrial object based on recurrent neural network
Author :
Jianping, Wei ; Huade, Li ; Ming, Sun ; Shaoyuan, Sun
Author_Institution :
Sch. of Inf. Eng., UST Beijing, China
Abstract :
This paper discusses the architecture and algorithm of a class of dynamical neural network, the Elman recurrent neural network (RNN). Based on this network an approach for modeling a nonlinear time-varying industrial object, the direct current arc, is proposed. Compared with other modeling method for the object, the model based on RNN is proved to have better performance
Keywords :
modelling; neural net architecture; production engineering computing; recurrent neural nets; Elman recurrent neural network; complex industrial object modeling; direct current arc; neural net architecture; nonlinear object; time-varying object; Educational institutions; Neural networks; Recurrent neural 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.2000.863394
