Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines
Liquid electrolytes or ionic liquids (ILs) are a new class of environmentally friendly solvents which is highly promising for refrigeration and air conditioning applications in chemical industrial processes.In this contribution, Least Square Support Vector Machine (LS-SVM) models have been utilized...
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doaj-9a0c2056a0b546b3b6a1fdeb1f78b75f2021-06-02T10:33:21ZengElsevierAin Shams Engineering Journal2090-44792018-12-019413031312Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector MachinesAlireza Baghban0Mohammad Bahadori1Alireza Samadi Lemraski2Alireza Bahadori3Young Researcher and Elite Club, Marvdasht Branch, Islamic Azad University, Marvdasht, IranSchool of Environment, Griffith University, Nathan, QLD, AustraliaDepartment of Gas Engineering, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology (PUT), P.O. Box 63431, Ahwaz, IranSchool of Environment, Science and Engineering, Southern Cross University, Lismore, NSW, Australia; Australian Oil and Gas Services, Pty Ltd, Lismore, NSW 2480, Australia; Corresponding author at: School of Environment, Science and Engineering, Southern Cross University, Lismore, NSW, Australia.Liquid electrolytes or ionic liquids (ILs) are a new class of environmentally friendly solvents which is highly promising for refrigeration and air conditioning applications in chemical industrial processes.In this contribution, Least Square Support Vector Machine (LS-SVM) models have been utilized to predict the solubility of ammonia in ILs as a function of molecular weight (MW), critical temperature (Tc) and critical pressure (Pc) of pure ILs over wide ranges of temperature, pressure, and concentration. To this end, 352 experimental data points were collected from the published papers. Moreover, to verify the accuracy of the proposed models, statistical analyses such as regression coefficient, mean square error (MSE), average absolute deviation (AAD), standard deviation (STD) and root mean square error (RMSE) have been conducted on the calculated values. The results show the excellent performance of LSSVM models to predict the solubility of ammonia in different liquid electrolytes. Keywords: Ammonia, Solubility, Ionic liquid, Support Vector Machinehttp://www.sciencedirect.com/science/article/pii/S2090447916301162 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alireza Baghban Mohammad Bahadori Alireza Samadi Lemraski Alireza Bahadori |
spellingShingle |
Alireza Baghban Mohammad Bahadori Alireza Samadi Lemraski Alireza Bahadori Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines Ain Shams Engineering Journal |
author_facet |
Alireza Baghban Mohammad Bahadori Alireza Samadi Lemraski Alireza Bahadori |
author_sort |
Alireza Baghban |
title |
Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines |
title_short |
Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines |
title_full |
Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines |
title_fullStr |
Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines |
title_full_unstemmed |
Prediction of solubility of ammonia in liquid electrolytes using Least Square Support Vector Machines |
title_sort |
prediction of solubility of ammonia in liquid electrolytes using least square support vector machines |
publisher |
Elsevier |
series |
Ain Shams Engineering Journal |
issn |
2090-4479 |
publishDate |
2018-12-01 |
description |
Liquid electrolytes or ionic liquids (ILs) are a new class of environmentally friendly solvents which is highly promising for refrigeration and air conditioning applications in chemical industrial processes.In this contribution, Least Square Support Vector Machine (LS-SVM) models have been utilized to predict the solubility of ammonia in ILs as a function of molecular weight (MW), critical temperature (Tc) and critical pressure (Pc) of pure ILs over wide ranges of temperature, pressure, and concentration. To this end, 352 experimental data points were collected from the published papers. Moreover, to verify the accuracy of the proposed models, statistical analyses such as regression coefficient, mean square error (MSE), average absolute deviation (AAD), standard deviation (STD) and root mean square error (RMSE) have been conducted on the calculated values. The results show the excellent performance of LSSVM models to predict the solubility of ammonia in different liquid electrolytes. Keywords: Ammonia, Solubility, Ionic liquid, Support Vector Machine |
url |
http://www.sciencedirect.com/science/article/pii/S2090447916301162 |
work_keys_str_mv |
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