| 基于LSSVM实现CO2转化率的软测量建模 |
| |
| 引用本文： | 范磊,张运陶.基于LSSVM实现CO2转化率的软测量建模[J].计算机与应用化学,2006,23(1):55-58. |
| |
| 作者姓名： | 范磊 张运陶 |
| |
| 作者单位： | 西华师范大学应用化学研究所,四川,南充,637002 |
| |
| 摘 要： | 将最小二乘支持向量机LSSVM用于中压联尿尿素生产中CO2转化率的软测量建模，并与BPNN、RBFNN模型进行比较，研究表明，最小二乘支持向量机建模快速、准确，泛化性能好。将该模型用于生产试验，预测结果与事后分析值的均方误差MSE〈0．006，最大绝对误差为0．2801，相对误差绝对值在0．1％以内的约占90％，最大相对误差绝对值仅为0.42％，模型表现稳定，效果令人满意。
|
| 关 键 词： | 最小二乘支持向量机 中压联尿装置 CO2转化率 软测量 |
| 文章编号： | 1001-4160（2006）01-55-58 |
| 收稿时间： | 2005-06-28 |
| 修稿时间： | 2005-06-282005-07-16 |
Modeling of soft sensing transformation efficiency of carbon dioxide based on LSSVM |
| |
| FAN Lei,ZHANG YunTao.Modeling of soft sensing transformation efficiency of carbon dioxide based on LSSVM[J].Computers and Applied Chemistry,2006,23(1):55-58. |
| |
| Authors: | FAN Lei ZHANG YunTao |
| |
| Affiliation: | Applied Chemistry Institute,China West Normal University,Nanchong, 637002, Sichuan, China |
| |
| Abstract: | Soft sensor modeling method based on Least Square SVM (LSSVM) is proposed in this paper. The sensor is used to predict the transformation efficiency of carbon dioxide in medium pressure diurea process. Compared with BPNN and RBFNN the research indicates that this method is featured with higher speed, more accuracy and better generalization ability and performance. The experiment results shows that the mean square errors of estimation outputs and analytical values are less than 0. 006, and about 90% absolute relative errors are less than 0.1%. The maximal absolute error is 0. 262 1, and the maximal absolute relative error is only 0. 42%. The model is stable and the result is satisfactory. |
| |
| Keywords: | LSSVM medium pressure diurea equipment transformation efficiency of carbon dioxide soft sensor |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
