Multiscale Bayesian PCA for robust process modeling of a Fischer–Tropsch bench scale process-Reference-Cited by-同舟云学术

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Multiscale Bayesian PCA for robust process modeling of a Fischer–Tropsch bench scale process

Published:2023-09 Issue: Volume:240 Page:104921
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Malluhi Byanne,Basha Nour,Fezai Radhia,Ibrahim Gasim,Choudhury Hanif A.,Challiwala Mohamed,Nounou Hazem,Elbashir Nimir,Nounou Mohamed

Funder

Qatar National Research Fund

Qatar Foundation

Publisher

Elsevier BV

Subject

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

Reference25 articles.

1. Perspectives on process monitoring of industrial systems;Severson;IFAC-Papers OnLine,2015

2. A review on data-driven process monitoring methods: Characterization and mining of industrial data;Ji;Processes,2022

3. Multi-scale modeling of fixed-bed Fischer Tropsch reactor;Ghouri;Comput. Chem. Eng.,2016

4. Data-driven process monitoring and fault analysis of reformer units in hydrogen plants: Industrial application and perspectives;Kumar;Comput. Chem. Eng.,2020

5. Statistical process monitoring with independent component analysis;Lee;J. Process Control,2004

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