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Original Articles

Application of Artificial Neural Network in the Residual Oil Hydrotreatment Process

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Pages 2075-2084 | Received 16 May 2008, Accepted 27 Sep 2008, Published online: 19 Oct 2009

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Masoud Sheikhi Kordkheili & Farshad Rahimpour. (2023) Artificial neural network and semi-empirical modeling of industrial-scale Gasoil hydrodesulfurization reactor temperature profile. Mathematics and Computers in Simulation 206, pages 198-215.
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Yakubu M. John, Mustafa A. Mustafa, Raj Patel & Iqbal M. Mujtaba. (2019) Parameter estimation of a six-lump kinetic model of an industrial fluid catalytic cracking unit. Fuel 235, pages 1436-1454.
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Hamdi A. Al-Jamimi, Sadam Al-Azani & Tawfik A. Saleh. (2018) Supervised machine learning techniques in the desulfurization of oil products for environmental protection: A review. Process Safety and Environmental Protection 120, pages 57-71.
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S. Alimohammadi, Javad Sayyad Amin & E. Nikooee. (2015) Estimation of asphaltene precipitation in light, medium and heavy oils: experimental study and neural network modeling. Neural Computing and Applications 28:4, pages 679-694.
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Ghaidaa S. Daood, Hamidon Basri, Johnson Stanslas, Hamid Reza Fard Masoumi & Mahiran Basri. (2015) Predicting the optimum compositions of a parenteral nanoemulsion system loaded with azithromycin antibiotic utilizing the artificial neural network model. RSC Advances 5:101, pages 82654-82665.
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Mani Safamirzaei & Hamid Modarress. (2011) Hydrogen solubility in heavy n-alkanes; modeling and prediction by artificial neural network. Fluid Phase Equilibria 310:1-2, pages 150-155.
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Aysar T. Jarullah, Iqbal M. Mujtaba & Alastair S. Wood. (2011) Kinetic parameter estimation and simulation of trickle-bed reactor for hydrodesulfurization of crude oil. Chemical Engineering Science 66:5, pages 859-871.
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