上海大学学报（英文版）
上海大學學報（英文版）
상해대학학보（영문판）
JOURNAL OF SHANGHAI UNIVERSITY (ENGLISH EDITION)
2006年
6期
531-534
,共4页
刘清坤%阙沛文%费春国%宋寿鹏
劉清坤%闕沛文%費春國%宋壽鵬
류청곤%궐패문%비춘국%송수붕
model selection%support vector machine (SVM)%mutative scale chaos optimization (MSCO)%ultrasonic testing (UT)%non-destructive testing (NDT)
This paper proposes a new search strategy using mutative scale chaos optimization algorithm (MSCO) for model selection of support vector machine (SVM). It searches the parameter space of SVM with a very high efficiency and finds the optimum parameter setting for a practical classification problem with very low time cost. To demonstrate the performance of the proposed method it is applied to model selection of SVM in ultrasonic flaw classification and compared with grid search for model selection. Experimental results show that MSCO is a very powerful tool for model selection of SVM, and outperforms grid search in search speed and precision in ultrasonic flaw classification.
