Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess

Fisher, O.J., Watson, N.J. orcid.org/0000-0001-5216-4873, Porcu, L. et al. (3 more authors) (2022) Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess. Biochemical Engineering Journal, 185. 108499. ISSN 1369-703X

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Item Type: Article
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© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords: Data-driven models; Bioprocess; Data volume; Data variability; Data visualisation
Dates:
  • Published: July 2022
  • Published (online): 30 May 2022
  • Accepted: 27 May 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > School of Food Science and Nutrition (Leeds) > FSN Nutrition and Public Health (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Jul 2024 13:59
Last Modified: 10 Jul 2024 13:59
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.bej.2022.108499
Open Archives Initiative ID (OAI ID):

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