Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess
(2022)
Journal Article
Fisher, O., Watson, N. J., Porcu, L., Bacon, D., Rigley, M., & Gomes, R. L. (2022). Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess. Biochemical Engineering Journal, 185, Article 108499. https://doi.org/10.1016/j.bej.2022.108499
Advances in industrial digital technologies have led to an increasing volume of data generated from industrial bioprocesses, which can be utilised within data-driven models (DDM). However, data volume and variability complications make developing mod... Read More about Data-driven modelling for resource recovery: Data volume, variability, and visualisation for an industrial bioprocess.