[1]刘国海,苏勇,杨铭,等.基于多准则和高斯过程回归的动态软测量建模方法[J].东南大学学报(自然科学版),2015,45(6):1086-1090.[doi:10.3969/j.issn.1001-0505.2015.06.011]
 Liu Guohai,Su Yong,Yang Ming,et al.Dynamic soft sensor modeling based on multi-criterion method and Gaussian process regression[J].Journal of Southeast University (Natural Science Edition),2015,45(6):1086-1090.[doi:10.3969/j.issn.1001-0505.2015.06.011]
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基于多准则和高斯过程回归的动态软测量建模方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第6期
页码:
1086-1090
栏目:
自动化
出版日期:
2015-11-20

文章信息/Info

Title:
Dynamic soft sensor modeling based on multi-criterion method and Gaussian process regression
作者:
刘国海苏勇杨铭梅从立
江苏大学电气信息工程学院, 镇江 212013
Author(s):
Liu Guohai Su Yong Yang Ming Mei Congli
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
关键词:
软测量 高斯过程回归 动态建模 模型定阶
Keywords:
soft sensor Gaussian process regression dynamic model model order
分类号:
TP13
DOI:
10.3969/j.issn.1001-0505.2015.06.011
摘要:
为了解决静态软测量建模预测精度低和鲁棒性差等问题,提出了一种基于多准则和高斯过程回归的动态软测量建模方法.该方法综合考虑多种模型定阶准则,提出了高斯过程回归动态软测量模型定阶策略,为模型阶数确定提供了依据,并将所提动态软测量模型应用于红霉素发酵过程中生物量浓度的估计. 研究结果表明,基于高斯过程回归的动态软测量建模方法可以实现对生物量浓度的高精度预测,且预测结果具有较小的置信度区间.
Abstract:
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.

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备注/Memo

备注/Memo:
收稿日期: 2015-05-05.
作者简介: 刘国海(1964—),男,博士,教授, ghliu@ujs.edu.cn.
基金项目: 江苏省自然科学基金资助项目(BK20130531)、江苏高校优势学科建设工程资助项目(PAPD)(2011[6]).
引用本文: 刘国海,苏勇,杨铭,等.基于多准则和高斯过程回归的动态软测量建模方法[J].东南大学学报:自然科学版,2015,45(6):1086-1090. [doi:10.3969/j.issn.1001-0505.2015.06.011]
更新日期/Last Update: 2015-11-20