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		Ling WANG,Zhichun MU,Hui GUO.[en_title][J].Control Theory and Technology,2005,3(3):230~234.[Copy]

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LingWANG,ZhichunMU,HuiGUO
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Received:June 23, 2004Revised:May 23, 2005

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Fuzzy rule-based support vector regression system

Ling WANG, Zhichun MU, Hui GUO

(Information Engineering School, University of Science and Technology,Beijing 100083,China)

Abstract:

In this paper,we design a fuzzy rule-based support vector regression system.The proposed system utilizes the advantages of fuzzy model and support vector regression to extract support vectors to generate fuzzy if-then rules from the training data set.Based on the first-order linear Tagaki-Sugeno (TS) model,the structure of rules is identified by the support vector regression and then the consequent parameters of rules are tuned by the global least squares method.Our model is applied to the real world regression task.The simulation results gives promising performances in terms of a set of fuzzy rules,which can be easily interpreted by humans.

Key words: TS fuzzy model Support vector machine Support vector regression