Modeling and prediction of activity coefficient ratio of electrolytes in aqueous electrolyte solution containing amino acids using artificial neural network

M.R. Dehghani; H. Modarress; A. Bakhshi

doi:10.1016/j.fluid.2006.04.003

Modeling and prediction of activity coefficient ratio of electrolytes in aqueous electrolyte solution containing amino acids using artificial neural network

Fluid Phase Equilibria ◽

10.1016/j.fluid.2006.04.003 ◽

2006 ◽

Vol 244 (2) ◽

pp. 153-159 ◽

Cited By ~ 19

Author(s):

M.R. Dehghani ◽

H. Modarress ◽

A. Bakhshi

Keyword(s):

Neural Network ◽

Amino Acids ◽

Artificial Neural Network ◽

Activity Coefficient ◽

Electrolyte Solution ◽

Aqueous Electrolyte ◽

Aqueous Electrolyte Solution ◽

Modeling And Prediction ◽

Activity Coefficient Ratio ◽

Artificial Neural

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Phase Equilibrium Involving Xylitol, Water, and Ethylene Glycol or 1,2-Propylene Glycol: Experimental Data, Activity Coefficient Modeling, and Prediction with Artificial Neural Network-Molecular Descriptors

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.8b02480 ◽

2018 ◽

Vol 57 (31) ◽

pp. 10675-10683 ◽

Cited By ~ 5

Author(s):

Patrícia G. Machado ◽

Alessandro C. Galvão ◽

Weber S. Robazza ◽

Pedro F. Arce ◽

Bruna E. Hochscheidt

Keyword(s):

Neural Network ◽

Experimental Data ◽

Artificial Neural Network ◽

Phase Equilibrium ◽

Activity Coefficient ◽

Ethylene Glycol ◽

Propylene Glycol ◽

Molecular Descriptors ◽

Modeling And Prediction ◽

Artificial Neural

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Aqueous viscosity of carbohydrates: Experimental data, activity coefficient modeling, and prediction with artificial neural network-molecular descriptors

Journal of Molecular Liquids ◽

10.1016/j.molliq.2020.114932 ◽

2021 ◽

Vol 322 ◽

pp. 114932

Author(s):

Karine Varnier ◽

Alessandro C. Galvão ◽

Pedro F. Arce ◽

Weber S. Robazza

Keyword(s):

Neural Network ◽

Experimental Data ◽

Artificial Neural Network ◽

Activity Coefficient ◽

Molecular Descriptors ◽

Modeling And Prediction ◽

Artificial Neural

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An artificial neural network supported stochastic process for degradation modeling and prediction

Reliability Engineering & System Safety ◽

10.1016/j.ress.2021.107738 ◽

2021 ◽

pp. 107738

Author(s):

Di Liu ◽

Shaoping Wang

Keyword(s):

Neural Network ◽

Stochastic Process ◽

Artificial Neural Network ◽

Degradation Modeling ◽

Modeling And Prediction ◽

Artificial Neural

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Applicability of artificial neural network for modeling and prediction of the laser polished surface quality

10.1364/cleo_at.2021.ath4p.3 ◽

2021 ◽

Author(s):

Honghe Wu ◽

Evgueni V. Bordatchev

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Surface Quality ◽

Polished Surface ◽

Modeling And Prediction ◽

Artificial Neural

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Hydrogen solubility in heavy n-alkanes; modeling and prediction by artificial neural network

Fluid Phase Equilibria ◽

10.1016/j.fluid.2011.08.004 ◽

2011 ◽

Vol 310 (1-2) ◽

pp. 150-155 ◽

Cited By ~ 16

Author(s):

Mani Safamirzaei ◽

Hamid Modarress

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Hydrogen Solubility ◽

Modeling And Prediction ◽

Artificial Neural

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Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method

Expert Systems with Applications ◽

10.1016/j.eswa.2010.11.041 ◽

2011 ◽

Vol 38 (5) ◽

pp. 5826-5832 ◽

Cited By ~ 183

Author(s):

İlhan Asiltürk ◽

Mehmet Çunkaş

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Multiple Regression ◽

Regression Method ◽

Turning Operations ◽

Modeling And Prediction ◽

Multiple Regression Method ◽

Artificial Neural

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Thermodynamic modeling of the KCl+formamide/glucose/proline+water ternary systems and activity coefficient prediction based on artificial neural network

Journal of Molecular Liquids ◽

10.1016/j.molliq.2015.03.028 ◽

2015 ◽

Vol 207 ◽

pp. 136-144 ◽

Cited By ~ 2

Author(s):

Bahram Ghalami-Choobar ◽

Behnam Ghalami Choobar

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Activity Coefficient ◽

Thermodynamic Modeling ◽

Ternary Systems ◽

Artificial Neural

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Developing an Artificial Neural Network for Modeling and Prediction of Temporal Structure and Spectral Composition of Environmental Noise in Cities

Artificial Neural Networks - Application ◽

10.5772/15476 ◽

2011 ◽

Author(s):

Antonio J. ◽

Diego P. ◽

Angel Ramos-Ridao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Temporal Structure ◽

Spectral Composition ◽

Environmental Noise ◽

Modeling And Prediction ◽

Artificial Neural

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Modeling and Prediction of Resistivity, Capillary Pressure and Relative Permeability Using Artificial Neural Network

10.2523/iptc-19854-ms ◽

2020 ◽

Author(s):

Mustafa Ba alawi ◽

Salem Gharbi ◽

Mohamed Mahmoud

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Capillary Pressure ◽

Relative Permeability ◽

Modeling And Prediction ◽

Artificial Neural

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Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

Pure and Applied Geophysics ◽

10.1007/s00024-011-0437-5 ◽

2011 ◽

Vol 169 (10) ◽

pp. 1891-1908 ◽

Cited By ~ 12

Author(s):

Surajit Chattopadhyay ◽

Goutami Chattopadhyay

Keyword(s):

Neural Network ◽

Principal Component Analysis ◽

Artificial Neural Network ◽

Total Ozone ◽

Principal Component ◽

Component Analysis ◽

Ozone Concentrations ◽

Modeling And Prediction ◽

Monthly Total ◽

Artificial Neural

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