Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]

Roshanak Agharafeie; Jorge M. Mendes; Rui Manuel Freitas Oliveira

Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]

Roshanak Agharafeie, Jorge M. Mendes, Rui Manuel Freitas Oliveira

Research output: Contribution to conference › Poster

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Abstract

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

Original language	English
Number of pages	1
Publication status	Unpublished - 27 Sept 2024
Event	Data Research Meetup by MagIC - NOVA Information Management School, Lisbon, Portugal Duration: 24 Sept 2024 → 24 Sept 2024 Conference number: 1 https://magic.novaims.unl.pt/en/society/events/data-research-meetup-by-magic/

Other

Other	Data Research Meetup by MagIC
Country/Territory	Portugal
City	Lisbon
Period	24/09/24 → 24/09/24
Internet address	https://magic.novaims.unl.pt/en/society/events/data-research-meetup-by-magic/

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Deep_Hybrid_Modelling_of_a_Supercritical_CO2_Extraction_ProcessFinal published version, 725 KBLicence: Unspecified

Best Scientific Poster Award 2024 from Data Research meetup by MagIC
Agharafeie, Roshanak (Recipient), 24 Sept 2024
Prize: Prize (including medals and awards)

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Deep Neural Network Modelling in Supercritical CO2 Extraction Process
Roshanak Agharafeie (Speaker), José Miguel Machado de Matos Pinto (Speaker), Pedro Miguel Calado Simões (Speaker), Jorge Morais Mendes (Speaker) & Rui Manuel Freitas Oliveira (Speaker)
4 Jul 2024
Activity: Talk or presentation › Oral presentation
Deep Hybrid Modelling of a Supercritical CO2 Extraction Process
Roshanak Agharafeie (Speaker), José Miguel Machado de Matos Pinto (Speaker), Pedro Miguel Calado Simões (Speaker), Jorge Morais Mendes (Speaker) & Rui Manuel Freitas Oliveira (Speaker)
22 Oct 2024
Activity: Talk or presentation › Oral presentation

Cite this

@conference{5a3f122de924433ea1db53b0c7c3d917,

title = "Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]",

abstract = "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",

author = "Roshanak Agharafeie and Mendes, {Jorge M.} and Oliveira, {Rui Manuel Freitas}",

note = "info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT# info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50006%2F2020/PT# https://doi.org/10.54499/UIDB/04152/2020# 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{\textquoteright}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 (Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia), under the project - UIDB/04152/2020 (DOI:10.54499/UIDB/04152/2020) - Centro de Investiga{\c c}{\~a}o em Gest{\~a}o de Informa{\c c}{\~a}o (MagIC)/NOVA IMS); Data Research Meetup by MagIC ; Conference date: 24-09-2024 Through 24-09-2024",

year = "2024",

month = sep,

day = "27",

language = "English",

url = "https://magic.novaims.unl.pt/en/society/events/data-research-meetup-by-magic/",

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TY - CONF

T1 - Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]

AU - Agharafeie, Roshanak

AU - Mendes, Jorge M.

AU - Oliveira, Rui Manuel Freitas

N1 - Conference code: 1

PY - 2024/9/27

Y1 - 2024/9/27

N2 - 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

AB - 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

M3 - Poster

T2 - Data Research Meetup by MagIC

Y2 - 24 September 2024 through 24 September 2024

ER -

Deep Hybrid Modelling of a Supercritical CO2 Extraction Process [poster]

Abstract

Other

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Prizes

Best Scientific Poster Award 2024 from Data Research meetup by MagIC

Activities

Deep Neural Network Modelling in Supercritical CO2 Extraction Process

Deep Hybrid Modelling of a Supercritical CO2 Extraction Process

Cite this