Variable Sub-Region Canonical Variate Analysis for Dynamic Process Monitoring
When all process variables are used to establish one data-based model, some variables have little contributions to the model. When these variables are grouped into a small local variable set to develop a data-based model, their contributions will become large. It is called local variable characteris...
Main Authors: | Yuping Cao, Lei Yu, Xiaogang Deng, Xiaoling Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9007427/ |
Similar Items
-
Extended Variational Message Passing for Automated Approximate Bayesian Inference
by: Semih Akbayrak, et al.
Published: (2021-06-01) -
Quality-Relevant Batch Process Fault Detection Using a Multiway Multi-Subspace CVA Method
by: Yuping Cao, et al.
Published: (2017-01-01) -
VIGoR: Variational Bayesian Inference for Genome-Wide Regression
by: Akio Onogi, et al.
Published: (2016-04-01) -
Rapid Identification of Phospholipase A<sub>2</sub> Transcripts from Snake Venoms
by: Ying Jia, et al.
Published: (2019-01-01) -
Robust spatio-temporal latent variable models
by: Christmas, Jacqueline
Published: (2011)