Dealing with Irregular Data in Soft Sensors: Bayesian Method and Comparative Study

Author:

Khatibisepehr Shima1,Huang Biao1

Affiliation:

1. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada T6G 2G6

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Reference36 articles.

1. Abony, J. ; Madar, J. , Szeifert, F.Combining First Principles Models and Neural Networks for Generic Model Control; 6th On-line World Conference on Soft Computing in Industrial Applications (WSC6); Internet, September 2001

2. Brandel, J.Empirical Bayes Methods for Missing Data Analysis;Technical Report 2004,11;Department of Mathematics, Uppsala University:Sweden, June 2004.

3. Champagne, M.; Amazouz, M. ; Platon, R.The Application of Soft Sensors in the Pulp and Paper and Cement Manufacturing Sectors for Process and Energy Performance Improvement; Technical Report CETC 2005−100(TR); Effective Assets Inc.: June, 2005.

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