Multiscale Latent Variable Regression
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, suc...
Saved in:
Main Authors: | Mohamed N. Nounou, Hazem N. Nounou |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2010-01-01
|
Series: | International Journal of Chemical Engineering |
Online Access: | http://dx.doi.org/10.1155/2010/935315 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Integrated Multiscale Latent Variable Regression and Application to Distillation Columns
by: Muddu Madakyaru, et al.
Published: (2013-01-01) -
Group Identification and Variable Selection in Quantile Regression
by: Ali Alkenani, et al.
Published: (2019-01-01) -
A data-driven latent variable approach to validating the research domain criteria framework
by: S. K. L. Quah, et al.
Published: (2025-01-01) -
Latent Error /
by: Ghasi, Samuel
Published: (2005) -
Multiscale Image Registration
by: Dana Paquin, et al.
Published: (2006-01-01)