Fault detection using Graph Neural Differential Auto-encoders (GNDAE)-Reference-Cited by-同舟云学术

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Fault detection using Graph Neural Differential Auto-encoders (GNDAE)

Published:2024-10 Issue: Volume:189 Page:108775
ISSN:0098-1354
Container-title:Computers & Chemical Engineering
language:en
Short-container-title:Computers & Chemical Engineering

Author:

Goswami Umang,Kodamana Hariprasad^ORCID,Ramteke Manojkumar^ORCID

Publisher

Elsevier BV

Reference77 articles.

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2. N2O emissions from activated sludge processes, 2008- 2009: results of a national monitoring survey in the United States;Ahn;Environ. Sci. Technol.,2010

3. Graph-based method for fault detection in the iron-making process;An;IEEE Access,2020

4. An explainable artificial intelligence based approach for interpretation of fault classification results from deep neural networks;Bhakte;Chem. Eng. Sci.,2022

5. Model-based parameter estimation for fault detection using multiparametric programming;Che Mid;Ind. Eng. Chem. Res.,2017

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