引用本文: | 贾润达,毛志忠,常玉清,周俊武.基于投影寻踪的非线性鲁棒偏最小二乘法及应用[J].控制理论与应用,2010,27(3):391~394.[点击复制] |
JIA Run-da,MAO Zhi-zhong,CHANG Yu-qing,ZHOU Jun-wu.Nonlinear robust partial least squares based on projection pursuit and its application[J].Control Theory and Technology,2010,27(3):391~394.[点击复制] |
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基于投影寻踪的非线性鲁棒偏最小二乘法及应用 |
Nonlinear robust partial least squares based on projection pursuit and its application |
摘要点击 2999 全文点击 1754 投稿时间:2008-09-17 修订日期:2009-04-11 |
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DOI编号 10.7641/j.issn.1000-8152.2010.3.CCTA081001 |
2010,27(3):391-394 |
中文关键词 径向基函数 投影寻踪 偏最小二乘法 鲁棒性 非线性 |
英文关键词 radial basis function projection pursuit partial least squares robustness nonlinear |
基金项目 国家“863”高技术研究发展计划资助项目(2006AA060201). |
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中文摘要 |
来自工业现场的数据往往具有非线性特性且包含离群点, 利用非线性偏最小二乘(partial least squares, PLS)建模易受离群点的影响. 针对这一问题, 结合径向基函数(radial basis function, RBF)网络, 本文提出了一种基于投影寻踪的非线性鲁棒PLS方法. 该方法首先利用RBF变换将自变量与因变间的非线性关系转化为线性关系; 然后利用投影寻踪算法提取变换后自变量的鲁棒偏最小二乘法成分; 最后建立鲁棒PLS成分与因变量之间的鲁棒线性回归模型. 将该方法应用于湿法冶金萃余液pH值软测量建模问题, 结果验证了其有效性. |
英文摘要 |
Data from industrial field usually possess nonlinear feature and contain outliers;modeling with nonlinear partial least squares(PLS) method may suffer from these outliers. For this case, combining with radial basis function(RBF) networks, we present a nonlinear robust PLS method based on the projection pursuit. First, the nonlinear relationship between independent and dependent variables is changed into a linear one by RBF transformation. Then, projection pursuit algorithm is employed to extract the robust PLS components of transformed independent variables. Finally a robust linear regression model is established between robust PLS components and the dependent variable. Applying the method to the soft-sensor modeling for pH value of raffinate solution in hydrometallurgy, we validate the effectiveness by the results. |