Title: Application of support vector machine in industrial process
Abstract: Support vector machine(SVM) is new learning machine based on statistical learning theory, which is a kind of learning algorithm focused on small sample. It has improved the ability of generation greatly and solved the over-fitting problem of neural network successfully by using the principle of structural risk minimization. Recently SVM has been used in the field of pattern recognition, however much less in the field of industrial process. This article firstly introduces the development of SVM from the following sides : theory research, algorithm configuration, parameter selection and expanding SVM, then analyzes the applications of SVM to industrial process, such as fault diagnosis, process modeling, system identification, and nonlinear control and so on. Finally, the future research directions are pointed out.
Publication Year: 2005
Publication Date: 2005-01-01
Language: en
Type: article
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Cited By Count: 1
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