Multilevel Modeling for Data Mining of Downstream Bio-Industrial Processes-Reference-Cited by-同舟云学术

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Multilevel Modeling for Data Mining of Downstream Bio-Industrial Processes

Published:2016-05 Issue: Volume:154 Page:62-71
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Klimkiewicz A.,Cervera-Padrell A.E.,van den Berg F.W.J.

Funder

Innovation Fund Denmark

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference22 articles.

1. The process chemometrics approach to process monitoring and fault detection;Wise;J. Process Control,1996

2. Application of latent variable methods to process control and multivariate statistical process control in industry;Kourti;Int J Adapt Control Signal Process,2005

3. Multivariate statistical monitoring of process operating performance;Kresta;Can. J. Chem. Eng.,1991

4. Multilevel component analysis and multilevel PLS of chemical process data;de Noord;J. Chemom.,2005

5. Multivariate dynamic data modeling for analysis and statistical process control of batch processes, start-ups and grade transitions;Kourti;J. Chemom.,2003

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1. Understanding Fouling in an Industrial Biorefinery Membrane Separation Process by Feature-Oriented Data-Driven Modeling;Industrial & Engineering Chemistry Research;2024-05-08

2. Hybrid modeling of a biorefinery separation process to monitor short-term and long-term membrane fouling;Chemical Engineering Science;2024-01

3. Troubleshooting high-pressure issues in an industrial biorefinery process by feature-oriented modeling;Computer Aided Chemical Engineering;2023

4. Prediction of Permeate Flux in Ultrafiltration Processes: A Review of Modeling Approaches;Membranes;2021-05-18

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