DocumentCode
1573039
Title
Modeling study of sludge process based on neural network
Author
Yu, Ying ; Qiao, Junfei ; Ye, Xudong
Author_Institution
Sch. of Electron. & Control Eng., Beijing Univ. of Technol., China
Volume
4
fYear
2004
Firstpage
3413
Abstract
On the basis of analyzing the classical methods of sludge process modeling, the paper put forward a new method about activated sludge process by neural networks. Firstly, the paper utilized principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors. Then built activated sludge process system by BP and RBF artificial neural networks, the applicability of the two neural network models were analyzed to sludge process. The experiment result shows that: (1) these neural networks may reflect real conditions correctly and have strong self-adaptation; (2) the RBF neural network model has better convergence ability and impending speed than the BP neural network model.
Keywords
backpropagation; principal component analysis; radial basis function networks; sludge treatment; RBF artificial neural networks; back propagation neural network; input vectors; principal component analysis; sludge process; Artificial neural networks; Control engineering; Convergence; Neural networks; Paper technology; Power supplies; Power system modeling; Principal component analysis; Sludge treatment;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1343176
Filename
1343176
Link To Document