[1]颜学峰.优化岭参数的非线性岭回归及4-CBA含量软测量[J].智能系统学报,2006,1(1):74-78.
YAN Xue-feng.Modified nonlinear ridge regression with optimal ridge pa rameter and its application to 4-CBA soft sensor[J].CAAI Transactions on Intelligent Systems,2006,1(1):74-78.
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YAN Xue-feng.Modified nonlinear ridge regression with optimal ridge pa rameter and its application to 4-CBA soft sensor[J].CAAI Transactions on Intelligent Systems,2006,1(1):74-78.
优化岭参数的非线性岭回归及4-CBA含量软测量
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
1
期数:
2006年第1期
页码:
74-78
栏目:
学术论文—人工智能基础
出版日期:
2006-03-25
- Title:
- Modified nonlinear ridge regression with optimal ridge pa rameter and its application to 4-CBA soft sensor
- 文章编号:
- 1673-4785(2006)01-0074-05
- Keywords:
- ridge regression; ridge parameter; evolution algorithm; soft sensor
- 分类号:
- O212.4
- 文献标志码:
- A
- 摘要:
- 针对二甲苯氧化反应过程中影响主要副产物对羧基苯甲醛含量的因素众多且呈高度非线性的问题，提出基于优化岭参数的非线性岭回归MNRR算法，并应用于建立4CBA含量软测量模型，获得满意的结果.MNRR采用非线性变换对原始模式特征空间进行扩张，以预测性能为指标，采用进化算法确定最佳岭参数，最终建立具有强非线性表达能力以及预测性能良好的模型.与非线性最小二乘回归和基于广义交叉有效性逐步估计岭参数的非线性岭回归相比，MNRR模型具有更高的预测精度且克服了传统岭回归算法最佳岭参数难以确定的缺点.
- Abstract:
- Considering that there exist many factors having high -nonlinear and co mplex effect on the concentration of the 4carboxybenzaldehyde (4-CBA) in prod uc t, which was the most important intermediate product of p-xylene oxidation reac ti on, a modified nonlinear ridge regression (MNRR) based on optimal ridge paramet er, was proposed to develop the 4-CBA concentration soft sensor. Satisfactory r e sults were obtained. Firstly, MNRR applied the nonlinear transformation for init ial pattern independent variables to expand pattern space. Secondly, considering that there exists correlation or multicollinearity among the variables in the e xpanding pattern space, the ridge regression was employed, in which evolution al gorithm was used to obtain the global optimal ridge parameter according to the p re dicting ability of the model. Thus, the model was obtained that can describe com plex nonlinear system and has good predict accuracy. The comparison results show that the MNRR model has better predict accuracy than nonlinear least square r egr ession and nonlinear ridge regression based on generalized cross-validation of s electing the ridge parameter. In addition, MNRR overcomes the main flaw in tradi tional ridge regression that is difficult to obtain the global optimal ridge pa rameter, and thus has the robust character.
- 参考文献/References:
-
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备注/Memo
收稿日期：2006-01-24.
基金项目：国家自然科学基金资助项目（20506003）；教育部科学技术研究重点基金资助项目（106073）；上海科技启明星基金资助项目（04QMX1433）.
作者简介：
颜学峰，副研究员，2002年6月获浙江大学控制理论与控制工程博士学位.主要研究方向：复杂系统建模与优化、智能信息处理.在国内外核心期刊上发表30余篇相关论文（其中10 余篇已被SCI、EI收录），曾获国家科技进步二等奖1项、省部级科技进步奖多项.
更新日期/Last Update:
2009-04-07