Modeling the activity coefficient at infinite dilution of water in ionic liquids using artificial neural networks and support vector machines

The activity coefficient at infinite dilution of water in ionic liquids is a thermodynamic property of a paramount importance in separation processes. However, accurate modeling of this parameter remains a challenging task due to the highly nonlinear behavior of the water/ionic liquid systems. Also,...

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Vydáno v:	Neural computing & applications Ročník 32; číslo 12; s. 8635 - 8653
Hlavní autoři:	Benimam, Hania, Si-Moussa, Cherif, Laidi, Maamar, Hanini, Salah
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.06.2020 Springer Nature B.V
Témata:	Activity coefficients Artificial Intelligence Artificial neural networks Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Correlation coefficients Data Mining and Knowledge Discovery Data points Dilution Graphical user interface Image Processing and Computer Vision Interpolation Ionic liquids Ions Learning theory Least squares Model accuracy Neural networks Original Article Probability and Statistics in Computer Science Regression analysis Sensitivity analysis Support vector machines Activity coefficient Ionic liquids Least square support vector machine Support vector machine Infinite dilution Artificial neural networks
ISSN:	0941-0643, 1433-3058
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