Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/173807| Título: | Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster] |
| Autor: | Agharafeie, Roshanak Mendes, Jorge M. Oliveira, Rui Manuel Freitas |
| Data: | 27-Set-2024 |
| Resumo: | Integrating deep learning and big data has the potential to significantly enhance efficiency in biomanufacturing. However, the industry currently faces a challenge due to inadequate big data infrastructure. A promising solution to this issue is the development of a hybrid neural network (HNN) that combines deep neural networks (DNN) with existing process knowledge |
| Descrição: | Agharafeie, R., Mendes, J. M., & Oliveira, R. M. F. (2024). Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]. Poster session presented at Data Research Meetup by MagIC, Lisbon, Portugal. --- This work was supported by the Associate Laboratory for Green Chemistry—LAQV, which is financed by national funds from FCT/MCTES (LA/P/0008/2020, UIDB/50006/2020 and UIDP/50006/2020). This work received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 101099487—BioLaMer-HORIZON-EIC-2022-PATHFINDEROPEN-01 (BioLaMer). This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 (DOI:10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS) |
| Peer review: | no |
| URI: | http://hdl.handle.net/10362/173807 |
| Aparece nas colecções: | NIMS: MagIC - Documentos de conferências nacionais |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| Deep_Hybrid_Modelling_of_a_Supercritical_CO2_Extraction_Process.pdf | 724,97 kB | Adobe PDF | Ver/Abrir |
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