| Issue |
E3S Web Conf.
Volume 592, 2024
International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2024)
|
|
|---|---|---|
| Article Number | 03018 | |
| Number of page(s) | 5 | |
| Section | Energy Production, Storage, and Distribution | |
| DOI | https://doi.org/10.1051/e3sconf/202459203018 | |
| Published online | 20 November 2024 | |
Neural networks for bioreactor control solutions
1 Federal Scientific Center for Biological Systems and Agricultural Technologies of the Russian Academy of Sciences, Orenburg 60000, Russia
2 Orenburg State University, Orenburg 460018, Russia
The use of machine learning has the potential to improve the control of bioreactors. The aim of this research was to use self-organising Kohonen maps based on algorithms built from the composition of the taxonomic structure of the bioreactor. By adjusting the weights of the map neurons, we can infer internal unobservable dependencies in the input data structures based on the results. Using our chosen model, we will gain a deeper understanding of the taxonomic composition of the bacterial community, which will allow us to better manage fermentation processes in bioreactors.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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