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《Chinese Journal of Analytical Chemistry》 2007-03
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Improved Weighted Least Squares Support Vector Machines Algorithm and Its Applications in Spectroscopic Quantitative Analysis

Lü Jian-Feng, Dai Lian-Kui (National Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou 310027)  
An improved algorithm of weighted least squares support vector machines (WLS-SVM) is proposed to overcome the negatine influence of abnornmal traningsamples on calibration models. The improved algorithm solves the iterative convergence problem in the original algorithm and has been used in spectroscopic quantitative analysis. Compared to the original algorithm, the experimental results show that the new algorithm remarkably improves model robustness and the ability to detect abnormal samples.
【Fund】: 国家高技术研究发展计划(863计划)项目(No.2006AA04Z169);; 浙江省科技计划项目(No.2005C311042)资助
【CateGory Index】: O657.3
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