Hybrid Process Models in Electrochemical Syntheses under Deep Uncertainty

Hybrid Process Models in Electrochemical Syntheses under Deep Uncertainty

Chemical process engineering and machine learning are merging rapidly, and hybrid process models have shown promising results in process analysis and process design. However, uncertainties in first-principles process models have an adverse effect on extrapolations and inferences based on hybrid proc...

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Bibliographic Details
Main Authors: Fenila Francis-Xavier, Fabian Kubannek, René Schenkendorf
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Processes
Subjects:
hybrid modeling
global parameter sensitivities
deep uncertainty
imprecise probabilities
point estimate method
neural ordinary differential equations
Online Access:https://www.mdpi.com/2227-9717/9/4/704

Internet

https://www.mdpi.com/2227-9717/9/4/704

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