DocumentCode
420559
Title
Dynamic system modeling based on rough sets and RBF neural networks
Author
Zhang, Tengfei ; Xiao, Jianmei
Author_Institution
Dept. of Electr. & Autom., Shanghai Maritime Univ., China
Volume
1
fYear
2004
fDate
15-19 June 2004
Firstpage
185
Abstract
Rough set is a powerful mathematical tool, which can deal with fuzzy and uncertain knowledge, and radial basis function (RBF) neural network has the ability to approach any nonlinear function precisely. A dynamic modeling method is presented using the rough sets and RBF network for complex system. The method is applied to model the steam turbine generators with complex dynamic characteristics and uncertainties. The simulation results prove the validity of this method.
Keywords
large-scale systems; modelling; nonlinear functions; radial basis function networks; rough set theory; steam turbines; turbogenerators; RBF neural networks; complex dynamic characteristics; complex dynamic uncertainties; complex system; dynamic system modeling method; nonlinear function; radial basis function; rough set theory; steam turbine generators; Character generation; Fuzzy neural networks; Fuzzy sets; Neural networks; Nonlinear dynamical systems; Power system modeling; Radial basis function networks; Rough sets; Turbines; Uncertainty;
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.2004.1340553
Filename
1340553
Link To Document