The research on application of sliding window LS-SVMin the batch process - 文章详情页

作者：

Sun, Xin (Sun, Xin.) | Jin Gao, Xue (Jin Gao, Xue.) | Yang Jia, Zhi (Yang Jia, Zhi.)

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EI Scopus

摘要：

This　paper　presents　an　improved　regression　algorithm　of　sliding　window　least　squares　support　vector　machine　(the　Sliding　Window　LS-SVM).　This　method　simplifies　the　data　within　the　sliding　window,　and　selects　the　similar　data　for　local　modeling　from　a　database　of　historical　batches　to　predict　the　data　within　the　sliding　window.　Combined　with　local　modeling,　the　improved　sliding　window　LS-SVM　algorithm　is　very　effective　to　predict　the　cell　concentration　in　the　penicillin　fermentation　process.　©　2013　AACC　American　Automatic　Control　Council.

关键词：

Support vector machines Batch data processing

作者机构：

[ 1 ] [Sun, Xin]College of Electronic Information and Control Engineering, Beijing University of Technology, China
[ 2 ] [Jin Gao, Xue]College of Electronic Information and Control Engineering, Beijing University of Technology, China
[ 3 ] [Yang Jia, Zhi]College of Electronic Information and Control Engineering, Beijing University of Technology, China

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