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Multiscale Latent Variable Regression
Joint Authors
Nounou, Hazem N.
Nounou, Mohamed N.
Source
International Journal of Chemical Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-03-30
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Engineering Sciences and Information Technology
Abstract EN
Multiscale wavelet-based representation of data has been shown to be a powerful tool in feature extraction from practical process data.
In this paper, this characteristic of multiscale representation is utilized to improve the prediction accuracy of some of the latent variable regression models, such as Principal Component Regression (PCR) and Partial Least Squares (PLS), by developing a multiscale latent variable regression (MSLVR) modeling algorithm.
The idea is to decompose the input-output data at multiple scales using wavelet and scaling functions, construct multiple latent variable regression models at multiple scales using the scaled signal approximations of the data and then using cross-validation, and select among all MSLVR models the model which best describes the process.
The main advantage of the MSLVR modeling algorithm is that it inherently accounts for the presence of measurement noise in the data by the application of the low-pass filters used in multiscale decomposition, which in turn improves the model robustness to measurement noise and enhances its prediction accuracy.
The advantages of the developed MSLVR modeling algorithm are demonstrated using a simulated inferential model which predicts the distillate composition from measurements of some of the trays' temperatures.
American Psychological Association (APA)
Nounou, Mohamed N.& Nounou, Hazem N.. 2010. Multiscale Latent Variable Regression. International Journal of Chemical Engineering،Vol. 2010, no. 2010, pp.1-8.
https://search.emarefa.net/detail/BIM-509473
Modern Language Association (MLA)
Nounou, Mohamed N.& Nounou, Hazem N.. Multiscale Latent Variable Regression. International Journal of Chemical Engineering No. 2010 (2010), pp.1-8.
https://search.emarefa.net/detail/BIM-509473
American Medical Association (AMA)
Nounou, Mohamed N.& Nounou, Hazem N.. Multiscale Latent Variable Regression. International Journal of Chemical Engineering. 2010. Vol. 2010, no. 2010, pp.1-8.
https://search.emarefa.net/detail/BIM-509473
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-509473