DocumentCode
1957538
Title
A C-means clustering based fuzzy modeling method
Author
Chang, Xiaoguang ; Li, Wei ; Farrell, Jay
Author_Institution
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume
2
fYear
2000
fDate
2000
Firstpage
937
Abstract
Proposes a neuro-fuzzy method to model the dynamic behavior of complex systems based on real experimental data. First, we investigate the firing strength of rules by a fuzzy C-means clustering method. Then, we retrieve the membership functions of input variables by a neuro-fuzzy network. Finally, we identify the parameters of linear local models by recursive least squares. In particular, we applied this method to construct the dynamics of a boiler combustion process
Keywords
boilers; fuzzy neural nets; large-scale systems; least squares approximations; modelling; pattern clustering; recursive estimation; C-means clustering; boiler combustion process; complex systems; dynamic behavior; firing strength; fuzzy modeling; linear local models; membership functions; neuro-fuzzy method; neuro-fuzzy network; recursive least squares; Boilers; Clustering algorithms; Combustion; Computer science; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Input variables; Least squares methods; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1098-7584
Print_ISBN
0-7803-5877-5
Type
conf
DOI
10.1109/FUZZY.2000.839158
Filename
839158
Link To Document