Dragonfly-Support Vector Machine for Regression Modeling of the Activity Coefficient at Infinite Dilution of Solutes in Imidazolium Ionic Liquids Using σ-Profile Descriptors

2020 ◽  
Vol 65 (6) ◽  
pp. 3161-3172 ◽  
Author(s):  
Hania Benimam ◽  
Cherif Si Moussa ◽  
Mohamed Hentabli ◽  
Salah Hanini ◽  
Maamar Laidi
Keyword(s):  
Support Vector Machine ◽  
Ionic Liquids ◽  
Activity Coefficient ◽  
Infinite Dilution ◽  
Regression Modeling ◽  
Support Vector ◽  
Imidazolium Ionic Liquids

Overview of Activity Coefficient of Thiophene at Infinite Dilution in Ionic Liquids and their Modeling Using COSMO-RS

2016 ◽  
Vol 55 (3) ◽  
pp. 788-797 ◽  
Author(s):  
Pranesh Matheswaran ◽  
Cecilia Devi Wilfred ◽  
Kiki A. Kurnia ◽  
Anita Ramli
Keyword(s):  
Ionic Liquids ◽  
Activity Coefficient ◽  
Infinite Dilution

Prediction of the binary surface tension of mixtures containing ionic liquids using Support Vector Machine algorithms

2015 ◽  
Vol 211 ◽  
pp. 534-552 ◽  
Author(s):  
Mohammad Hashemkhani ◽  
Reza Soleimani ◽  
Hossein Fazeli ◽  
Moonyong Lee ◽  
Alireza Bahadori ◽  
...  
Keyword(s):  
Surface Tension ◽  
Support Vector Machine ◽  
Ionic Liquids ◽  
Support Vector

Determination of the speed of sound in ionic liquids using a least squares support vector machine group contribution method

2014 ◽  
Vol 367 ◽  
pp. 188-193 ◽  
Author(s):  
Mehdi Sattari ◽  
Farhad Gharagheizi ◽  
Poorandokht Ilani-Kashkouli ◽  
Amir H. Mohammadi ◽  
Deresh Ramjugernath
Keyword(s):  
Support Vector Machine ◽  
Ionic Liquids ◽  
Least Squares ◽  
Speed Of Sound ◽  
Group Contribution ◽  
Support Vector ◽  
Group Contribution Method ◽  
Machine Group

Prediction of ionic conductivity of imidazolium-based ionic liquids at different temperatures using multiple linear regression and support vector machine algorithms

2021 ◽  
Vol 45 (39) ◽  
pp. 18584-18597
Author(s):  
Zi Kang Koi ◽  
Wan Zaireen Nisa Yahya ◽  
Kiki Adi Kurnia
Keyword(s):  
Support Vector Machine ◽  
Ionic Liquids ◽  
Ionic Conductivity ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Model Building ◽  
Support Vector ◽  
Different Temperatures ◽  
Stepwise Model Building

The conductivity of various imidazolium-based ILs has been predicted via QSPR approach using MLR and SVM regression coupled with stepwise model-building. This will aid the screening of suitable ILs with desired conductivity for specific applications.

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