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

Mani Safamirzaei; Hamid Modarress

doi:10.1016/j.fluid.2011.08.004

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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Hydrogen solubility in model components of Shenhua coal liquefaction oil: Modeling and prediction by an artificial neural network

Energy Sources Part A Recovery Utilization and Environmental Effects ◽

10.1080/15567036.2016.1258443 ◽

2017 ◽

Vol 39 (7) ◽

pp. 720-725

Author(s):

H. Luo ◽

Y. Qiao

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Coal Liquefaction ◽

Hydrogen Solubility ◽

Modeling And Prediction ◽

Artificial Neural ◽

Model Components

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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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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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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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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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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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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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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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Modeling and Prediction of Hourly Ambient Ozone (O3) and Oxides of Nitrogen (NOx) Concentrations Using Artificial Neural Network and Decision Tree Algorithms for an Urban Intersection in India

Journal of Hazardous Toxic and Radioactive Waste ◽

10.1061/(asce)hz.2153-5515.0000270 ◽

2016 ◽

Vol 20 (4) ◽

Cited By ~ 3

Author(s):

Chandrra Sekar ◽

C. S. P. Ojha ◽

B. R. Gurjar ◽

Manish Kumar Goyal

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Decision Tree ◽

Oxides Of Nitrogen ◽

Ambient Ozone ◽

Modeling And Prediction ◽

Tree Algorithms ◽

Artificial Neural

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