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
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;
Conference_Titel :
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-5877-5
DOI :
10.1109/FUZZY.2000.839158
