Dynamic soft sensor modeling based on multi-criterion method and Gaussian process regression

被引：1

作者：

Liu, Guohai ^{[1
]}

Su, Yong ^{[1
]}

Yang, Ming ^{[1
]}

Mei, Congli ^{[1
]}

机构：

[1] School of Electrical and Information Engineering, Jiangsu University, Zhenjiang

来源：

Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2015年 / 45卷 / 06期

关键词：

Dynamic model; Gaussian process regression; Model order; Soft sensor;

D O I：

10.3969/j.issn.1001-0505.2015.06.011

中图分类号：

学科分类号：

摘要：

A dynamic soft sensor modeling method based on multi-criterion method and Gaussian process regression is presented to overcome the problems of low prediction accuracy and poor robustness in static soft sensors. The multi-criterion method, as a theoretical basis of determing model order, takes into account several traditional criterions. The application of the proposed soft sensor to an erythromycin fermentation process is presented. Results show that the proposed dynamic soft sensor has high prediction accuracy and small predicted confidence intervals. © 2015, Southeast University. All right reserved.

引用

页码：1086 / 1090

页数：4

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