A New Soft Sensor Modeling Method Based on Modified AdaBoost with Incremental Learning

被引：1
|
作者：
Tian, Huixin [1 ]
Wang, Anna [2 ]
Mao, Zhizhong [2 ]
机构：
[1] Tianjin Polytech Univ, Elect & Automat Engn Dept, Tianjin, Peoples R China
[2] Northeastern Univ, Informat Sci & Engn Dept, Shenyang, Peoples R China
来源：
PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009) | 2009年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1109/CDC.2009.5400292
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Aiming at the characteristics of soft sensors, an ensemble learning algorithm AdaBoost.RT is used to establish the soft sensor models. According to the shortcoming of AdaBoost.RT and the difficulties of on-line updating for soft sensor models, a self-adaptive modifying threshold phi and an incremental learning method are proposed for improving the performance of original AdaBoost.RT. The new modified AdaBoostRT can overcome the disadvantages of original AdaBoost.RT and update the soft sensor model in real time. The new method is used to establish the soft sensor model of molten steel temperature in 300t LF. Practical production data are used to test the model. The results demonstrate that the new soft sensor model based on modified AdaBoost.RT can improve the prediction accuracy and has good ability of update.
引用
收藏
页码：8375 / 8380
页数：6
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