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Nabil Touzout

As seen in: MDPI, ACS Publications
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Articles

Interpretable Yield Prediction of Supercritical CO2 Extraction from Various Essential Oil Sources Using Optimized Machine Learning and PCA-Based Descriptors

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By Mohamed Hentabli, Nabil Touzout, Mohamed Kouider Amar, Ilhem Bouaziz
| ACS Publications
Cite Jump to ExpandCollapse Machine Learning and Deep LearningDecember 14, 2025 Interpretable Yield Prediction of Supercritical CO2 Extraction from Various Essential Oil Sources Using Optimized Machine Learning and PCA-Based Descriptors Click to copy article linkArticle link copied! Mohamed Kouider Amar Mohamed Kouider Amar Laboratory of Biomaterials and Transfer Phenomena, Theoretical and Computational Chemistry in Process Engineering Team, Faculty of Technology, University Yahia Fares of...
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Interpretable Yield Prediction of Supercritical CO2 Extraction from Various Essential Oil Sources Using Optimized Machine Learning and PCA-Based Descriptors

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By Mohamed Kouider Amar, Mohamed Hentabli, Nabil Touzout, Ilhem Bouaziz
| dx.doi.org
Machine Learning and Deep LearningDecember 14, 2025 Mohamed Kouider Amar Laboratory of Biomaterials and Transfer Phenomena, Theoretical and Computational Chemistry in Process Engineering Team, Faculty of Technology, University Yahia Fares of Medea, 26000 Medea, Algeria Mohamed Hentabli Laboratory of Biomaterials and Transfer Phenomena, Theoretical and Computational Chemistry in Process Engineering Team, Faculty of Technology, University Yahia Fares of Medea, 26000 Medea, Algeria Process...
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Harnessing Deep Learning for Real-Time Water Quality Assessment: A Sustainable Solution

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By Selma Toumi, Sabrina Lekmine, Nabil Touzout, Hamza Moussa
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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