Title :
Research on input variable selection for numeric data based fuzzy modeling
Author :
Xing, Zongyi ; Jia, Li-min ; Qin, Yong ; Lei, Tao
Author_Institution :
China Acad. of Railway Sci., Beijing, China
Abstract :
The first step to system modeling and control is input variable selection. Based on fast fuzzy modeling algorithm and input variable selection criterion, a simple and effective method for selecting input variables when building a Takagi-Sugeno fuzzy model is proposed. This method is applied to two well-known benchmark examples. Simulation results clearly show the effectiveness of the algorithm.
Keywords :
fuzzy set theory; modelling; pattern clustering; T-S fuzzy model; Takagi-Sugeno fuzzy model; fast fuzzy modeling algorithm; input variable selection; numeric data based fuzzy modeling; system control; system modeling; Clustering algorithms; Control system synthesis; Fuzzy control; Fuzzy sets; Fuzzy systems; Inference algorithms; Input variables; Modeling; Rail transportation; Takagi-Sugeno model;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1260008
