A reinforcement learning-based hybrid modeling framework for bioprocess kinetics identification

Autor: Max R. Mowbray, Chufan Wu, Alexander W. Rogers, Ehecatl A. Del Rio‐Chanona, Dongda Zhang

Publikováno v: Mowbray, M R, Wu, C, Rogers, A W, Rio-Chanona, E A D & Zhang, D 2023, ' A reinforcement learning-based hybrid modeling framework for bioprocess kinetics identification ', Biotechnology and Bioengineering, vol. 120, no. 1, pp. 154-168 . https://doi.org/10.1002/bit.28262

Constructing predictive models to simulate complex bioprocess dynamics, particularly time-varying (i.e., parameters varying over time) and history-dependent (i.e., current kinetics dependent on historical culture conditions) behavior, has been a long

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81c14da3a470052a8567632cc06f5f37
https://uom.elsevierpure.com/en/publications/137e6d55-792a-447b-94b9-c09484add6fa

Machine Learning and Hybrid Modelling for Reaction Engineering : Theory and Applications

Autor: Dongda Zhang, Ehecatl Antonio del Río Chanona

Over the last decade, there has been a significant shift from traditional mechanistic and empirical modelling into statistical and data-driven modelling for applications in reaction engineering. In particular, the integration of machine learning and