Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine

李修亮; 苏宏业; 褚健

doi:10.1016/S1004-9541(09)60039-2

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Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine

Updated：2026-01-06

- Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine
- Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine
- 中国化学工程学报（英文版） 2009年17卷第1期页码：95-99
- Affiliations：
  
  National Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University,Hangzhou,China,310027
- Author bio：
- Funds：
  
  Supported by the National High Technology Research and Development Program of China (2006AA040309);National BasicResearch Program of China (2007CB714000)
- DOI：10.1016/S1004-9541(09)60039-2
  中图分类号：
- 纸质出版：2009
- Accepted：
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李修亮, 苏宏业, 褚健. Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine[J]. 中国化学工程学报（英文版）, 2009,17(1):95-99.

LI Xiuliang, SU Hongye, CHU Jian. Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine[J]. , 2009, 17(1): 95-99.
李修亮, 苏宏业, 褚健. Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine[J]. 中国化学工程学报（英文版）, 2009,17(1):95-99. DOI： 10.1016/S1004-9541(09)60039-2.

LI Xiuliang, SU Hongye, CHU Jian. Multiple Model Soft Sensor Based on Affinity Propagation, Gaussian Process and Bayesian Committee Machine[J]. , 2009, 17(1): 95-99. DOI： 10.1016/S1004-9541(09)60039-2.

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 chemical processes.

Abstract

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

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