A JITL-Based Probabilistic Principal Component Analysis for Online Monitoring of Nonlinear Processes-Reference-Cited by-同舟云学术

A JITL-Based Probabilistic Principal Component Analysis for Online Monitoring of Nonlinear Processes

Published:2018-10-20 Issue:10 Volume:51 Page:874-889
ISSN:0021-9592
Container-title:JOURNAL OF CHEMICAL ENGINEERING OF JAPAN
language:en
Short-container-title:J. Chem. Eng. Japan / JCEJ

Author:

Wang Ziyang¹,Liang Jun¹

Affiliation:

1. State Key Lab of Industrial Control Technology, Institute of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University

Publisher

Society of Chemical Engineers, Japan

Subject

General Chemical Engineering,General Chemistry

Link

https://www.jstage.jst.go.jp/article/jcej/51/10/51_17we309/_pdf

Reference30 articles.

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3. Chen, Q., U. Kruger and A. T. Leung; “Regularised Kernel Density Estimation for Clustered Process Data,” Control Eng. Pract., 12, 267–274 (2004)

4. Chen, T., E. Martin and G. Montague; “Robust Probabilistic PCA with Missing Data and Contribution Analysis for Outlier Detection,” Comput. Stat. Data Anal., 53, 3706–3716 (2009)

5. Cheng, C. and M. S. Chiu; “Nonlinear Process Monitoring Using JITL-PCA,” Chemometr. Intell. Lab., 76, 1–13 (2005)

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