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首页> 中文期刊> 《中国化学工程学报（英文版）》 >基于仿射聚类、高斯过程和贝叶斯决策的多模型软测量建模

基于仿射聚类、高斯过程和贝叶斯决策的多模型软测量建模

         
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摘要

Presented is a multiple model soft sensing method based on Affinity Propagation (AP), Gaussian process (GP) and Bayesian committee machine (BCM). AP clustering arithmetic is used to cluster training samples according to their operating points. Then, the sub-models are estimated by Gaussian Process Regression (GPR). Finally, in order to get a global probabilistic prediction, Bayesian committee machine is used to combine the outputs of the sub-estimators. The proposed method has been applied to predict the light naphtha end point in hydrocracker fractionators. Practical applications indicate that it is useful for the online prediction of quality monitoring in chemi-cal processes.

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  • 来源
    《中国化学工程学报（英文版）》 |2009年第1期|95-99|共5页
  • 作者

    李修亮; 苏宏业; 褚健;

  • 作者单位

    National Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;

    National Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;

    National Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;

  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 化工过程（物理过程及物理化学过程）;
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