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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Main Authors: Alireza Baghban, Mohammad Bahadori, Alireza Samadi Lemraski, Alireza Bahadori
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:Ain Shams Engineering Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447916301162
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spelling 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
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AT alirezasamadilemraski predictionofsolubilityofammoniainliquidelectrolytesusingleastsquaresupportvectormachines
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