Development of a LSSVM-GC model for estimating the electrical conductivity of ionic liquids

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• 作者：Farhad Gharagheizi ; Poor ; okht Ilani-Kashkouli ; Mehdi Sattari ; Amir H. Mohammadi ; Deresh Ramjugernath ; Dominique Richon
• 关键词：Electrical conductivity ; Support vector machine ; Ionic liquids ; Group contribution ; Model ; Database
• 刊名：Chemical Engineering Research and Design
• 出版年：January, 2014
• 年：2014
• 卷：92
• 期：1
• 页码：66-79
• 全文大小：1411 K

文摘

In this communication, an extensive set of 1077 experimental electrical conductivity data for 54 ionic liquids (ILs) was collected from 21 different literature sources. Using this dataset, a reliable least square support vector machine-group contribution (LSSVM-GC) model has been developed, which employs a total of 22 sub-structures in addition to the temperature to represent/predict the electrical conductivity of ILs. In order to distinguish the effects of the anion and cation on the electrical conductivity of ILs, 11 sub-structures related to the chemical structure of anions, and 11 sub-structures related to the chemical structure of cations were implemented. The proposed model produces a low average absolute relative deviation (AARD) of less than 3.3% taking into consideration all 1077 experimental data values.