Artificial Neural Network and Support Vector Regression Applied in Quantitative Structure-property Relationship Modelling of Solubility of Solid Solutes in Supercritical CO2

Artificial Neural Network and Support Vector Regression Applied in Quantitative Structure-property Relationship Modelling of Solubility of Solid Solutes in Supercritical CO2

In this study, the solubility of 145 solid solutes in supercritical CO2 (scCO2) was correlated using computational intelligence techniques based on Quantitative Structure-Property Relationship (QSPR) models. A database of 3637 solubility values has been collected from previously published papers. Dr...

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Bibliographic Details
Main Authors: Mohammed Moussaoui, Maamar Laidi, Salah Hanini, Mohamed Hentabli
Format: Article
Language:English
Published: Croatian Society of Chemical Engineers 2020-11-01
Series:Kemija u Industriji
Subjects:
solubility
solid solutes
supercritical-fluids
computational intelligence techniques
quantitative structure-property relationship
Online Access:http://silverstripe.fkit.hr/kui/assets/Uploads/3-611-630.pdf

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http://silverstripe.fkit.hr/kui/assets/Uploads/3-611-630.pdf

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