Multimode process data modeling: A Dirichlet process mixture model based Bayesian robust factor analyzer approach-Reference-Cited by-同舟云学术

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Multimode process data modeling: A Dirichlet process mixture model based Bayesian robust factor analyzer approach

Published:2015-03 Issue: Volume:142 Page:231-244
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Zhu Jinlin,Ge Zhiqiang,Song Zhihuan

Funder

National Natural Science Foundation of China

Project National 973

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference52 articles.

1. Fault Detection and Diagnosis in Industrial Systems;Chiang,2001

2. On-line monitoring of batch processes using a PARAFAC representation;Meng;J. Chemom.,2003

3. A new multivariate statistical process monitoring method using principal component analysis;Kano;Comput. Chem. Eng.,2001

4. Mechanical stability of monolithic catalysts: factors affecting washcoat adhesion and cohesion during preparation;Wu;AICHE J.,2014

5. Mixtures of probabilistic principal component analyzers;Tipping;Neural Comput.,1999

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