SVM-based fuzzy modeling for the arc welding process

Abstract

This paper proposes a fuzzy modeling method based on support vector machine (SVM) for the arc welding process. SVM provides a mechanism to extract support vectors for generating fuzzy IF-THEN rules from training data. In the proposed SVM-based fuzzy system (SVM-FS), SVM is used to extract IF-THEN rules; the fuzzy basis function inference system is adopted as the fuzzy inference system. So the approach possesses good comprehensibility as well as satisfactory generalization capability. Modeling is one of the key techniques in the automatic control of the arc welding process, and is still a very difficult problem. We give the main steps of modeling for the process using SVM-FS, including selecting input/output variables, acquiring raw data, extracting fuzzy rules and fuzzy inference. Experimental results show that the proposed approach outperforms the rough set method.