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Machine Learning for Societal Improvement, Modernization, and Progress
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Experimental investigation and ANN modelling on CO2 hydrate kinetics in multiphase pipeline systems
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Integration of Physical Examination, Old and New Biomarkers, and Ultrasonography by Using Neural Networks for Pediatric Appendicitis
Prediction of natural gas hydrates formation using a combination of thermodynamic and neural network modeling
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Reliable modeling of constant volume depletion (CVD) behaviors in gas condensate reservoirs
Adel Najafi-Marghmaleki, Afshin Tatar, Ali Barati-Harooni, Milad Arabloo, Shahin Rafiee-Taghanaki and Amir H. Mohammadi Fuel 231 146 (2018) https://doi.org/10.1016/j.fuel.2018.04.130
Multi-Objective Optimization of Microemulsion Flooding for Chemical Enhanced Oil Recovery
Mohammad Saber Karambeigi, Ali Haghighi Asl and Masoud Nasiri Oil & Gas Sciences and Technology – Revue d’IFP Energies nouvelles 73 4 (2018) https://doi.org/10.2516/ogst/2017032
A new methodology for the production of furfural as a renewable energy source from bagasse in acidic aqueous media
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Development of a least squares support vector machine model for prediction of natural gas hydrate formation temperature
Experimental Optimization and Modeling of Sodium Sulfide Production from H2S-Rich Off-Gas via Response Surface Methodology and Artificial Neural Network
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Prediction of sand production onset in petroleum reservoirs using a reliable classification approach
Vapor liquid equilibrium prediction of carbon dioxide and hydrocarbon systems using LSSVM algorithm
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Thermodynamic modeling of the KCl+formamide/glucose/proline+water ternary systems and activity coefficient prediction based on artificial neural network
Prediction of Methane Uptake on Different Adsorbents in Adsorbed Natural Gas Technology Using a Rigorous Model
Ebrahim Soroush, Mohammad Mesbah, Amin Shokrollahi, Alireza Bahadori and Mohammad Hossein Ghazanfari Energy & Fuels 28(10) 6299 (2014) https://doi.org/10.1021/ef501550p
Experimental Study and Intelligent Modeling of Density of Crude Oils Diluted with Solvents
Experimental Measurements and Correlations of Excess Molar Enthalpies for the Binary and Ternary Mixtures of (Cyclohexane, 1,4-Dioxane and Piperidine) or (Cyclohexane, Morpholine and Piperidine) at 308.15 K and Atmospheric Pressure
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Modeling and optimization of cross-flow ultrafiltration using hybrid neural network-genetic algorithm approach
Experimental study of natural gas hydrates and a novel use of neural network to predict hydrate formation conditions
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Robust Model for the Determination of Wax Deposition in Oil Systems
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Gas Hydrate Phase Equilibrium in Porous Media: Mathematical Modeling and Correlation
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Group contribution model for determination of molecular diffusivity of non-electrolyte organic compounds in air at ambient conditions
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Phase equilibrium modeling of clathrate hydrates of methane, carbon dioxide, nitrogen, and hydrogen+water soluble organic promoters using Support Vector Machine algorithm
Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure–Property Relationship Strategy
Farhad Gharagheizi, Ali Eslamimanesh, Farhad Farjood, Amir H. Mohammadi and Dominique Richon Industrial & Engineering Chemistry Research 50(19) 11382 (2011) https://doi.org/10.1021/ie200962w
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An accurate model for prediction of autoignition temperature of pure compounds
Determination of Critical Properties and Acentric Factors of Pure Compounds Using the Artificial Neural Network Group Contribution Algorithm
Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi and Dominique Richon Journal of Chemical & Engineering Data 56(5) 2460 (2011) https://doi.org/10.1021/je200019g
Representation and Prediction of Molecular Diffusivity of Nonelectrolyte Organic Compounds in Water at Infinite Dilution Using the Artificial Neural Network-Group Contribution Method
Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi and Dominique Richon Journal of Chemical & Engineering Data 56(5) 1741 (2011) https://doi.org/10.1021/je101190p
Use of Artificial Neural Network-Group Contribution Method to Determine Surface Tension of Pure Compounds
Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi and Dominique Richon Journal of Chemical & Engineering Data 56(5) 2587 (2011) https://doi.org/10.1021/je2001045
Artificial Neural Network Modeling of Solubilities of 21 Commonly Used Industrial Solid Compounds in Supercritical Carbon Dioxide
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Determination of Parachor of Various Compounds Using an Artificial Neural Network−Group Contribution Method
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Representation/Prediction of Solubilities of Pure Compounds in Water Using Artificial Neural Network−Group Contribution Method
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Phase Equilibrium Modeling of Structure H Clathrate Hydrates of Methane + Water “Insoluble” Hydrocarbon Promoter Using QSPR Molecular Approach
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Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds
Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi and Dominique Richon Industrial & Engineering Chemistry Research 50(17) 10344 (2011) https://doi.org/10.1021/ie201002e
Handling a very large data set for determination of surface tension of chemical compounds using Quantitative Structure–Property Relationship strategy
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Artificial Neural Network modeling of solubility of supercritical carbon dioxide in 24 commonly used ionic liquids
Ali Eslamimanesh, Farhad Gharagheizi, Amir H. Mohammadi and Dominique Richon Chemical Engineering Science 66(13) 3039 (2011) https://doi.org/10.1016/j.ces.2011.03.016
Hydrate phase equilibria for hydrogen+water and hydrogen+tetrahydrofuran+water systems: Predictions of dissociation conditions using an artificial neural network algorithm
Excess Molar Enthalpies for the Binary and Ternary Mixtures of Cyclohexane, Tetrahydropyran, and Piperidine at 308.15 K and Atmospheric Pressure: Experimental Measurements and Correlations
Farid B. Belaribi, Ghénima Boukais-Belaribi, Amir H. Mohammadi and Dominique Richon Journal of Chemical & Engineering Data 55(1) 303 (2010) https://doi.org/10.1021/je900347f
Extension of an Artificial Neural Network Algorithm for Estimating Sulfur Content of Sour Gases at Elevated Temperatures and Pressures
Mehdi Mehrpooya, Amir H. Mohammadi and Dominique Richon Industrial & Engineering Chemistry Research 49(1) 439 (2010) https://doi.org/10.1021/ie900399b
Experimental Measurements and Correlations of Excess Molar Enthalpies for the Binary and Ternary Mixtures of (Cyclohexane, Tetrahydropyran, and Morpholine) or (Cyclohexane, 1,4-Dioxane, and Morpholine) at 308.15 K and Atmospheric Pressure
Farid B. Belaribi, Atika Dahmoun, Aomar Dahmani, et al. Journal of Chemical & Engineering Data 55(8) 2833 (2010) https://doi.org/10.1021/je9010097
Development of Predictive Techniques for Estimating Liquid Water‐Hydrate Equilibrium of Water‐Hydrocarbon System
Excess Molar Enthalpies for the Binary and Ternary Mixtures of Cyclohexane, Tetrahydropyran, and 1,4-Dioxane at 308.15 K and Atmospheric Pressure: Experimental Measurements and Correlations
Ghénima Boukais-Belaribi, Amir H. Mohammadi, Farid B. Belaribi and Dominique Richon Journal of Chemical & Engineering Data 54(9) 2513 (2009) https://doi.org/10.1021/je900077g
A Mathematical Model Based on Artificial Neural Network Technique for Estimating Liquid Water−Hydrate Equilibrium of Water−Hydrocarbon System
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Estimating Sulfur Content of Hydrogen Sulfide at Elevated Temperatures and Pressures Using an Artificial Neural Network Algorithm
Amir H. Mohammadi and Dominique Richon Industrial & Engineering Chemistry Research 47(21) 8499 (2008) https://doi.org/10.1021/ie8004463