DSpace À propos de l'application DSpace
 

Depot Institutionnel de l'UMBB >
Publications Scientifiques >
Publications Internationales >

Veuillez utiliser cette adresse pour citer ce document : http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/5998

Titre: Application of gene expression programming for predicting density of binary and ternary mixtures of ionic liquids and molecular solvents
Auteur(s): Nait Amar, Menad
Ghriga, Mohammed Abdelfetah
Hemmati-Sarapardeh, Abdolhossein
Mots-clés: Ionic liquid
Density
Thermophysical properties
Modeling
Data-driven
Date de publication: 2020
Editeur: ELSEVIER
Collection/Numéro: Journal of the Taiwan Institute of Chemical Engineers;
Résumé: Ionic Liquids (ILs) have received increased attention across a number of disciplines in recent years. This noticeable importance of ILs is attributed to their attractive proprieties. Precise evaluation of the thermophysical properties of ionic liquids and their mixtures with molecular solvents is essential for distinct multidisciplinary applications. In this study, a rigorous white-box intelligent technique, viz. gene expression programming (GEP) was implemented for establishing new correlations for accurate prediction of density of binary and ternary mixtures of ILs and molecular solvents. The newly suggested correlations were developed using a comprehensive experimental database with 1985 real measurements under a variety of operational conditions. The obtained results revealed that the newly established GEP-based correlations can predict the density of binary and ternary mixtures of ILs and molecular solvents with a high degree of integrity. The GEP-based correlations exhibited overall average absolute relative error (AARE) values of 0.5621% and 0.2128% for binary and ternary cases, respectively. Besides, it was found that our proposed explicit correlations followed the expected tendency with respect to the considered variables. Furthermore, the superiority and the reliability of the GEP-based correlations was testified against the best-existing approaches in the literature. Finally, the leverage approach was performed and the statistical validity of the correlations and the experimental data was testified.
URI/URL: https://doi.org/10.1016/j.jtice.2020.11.029
https://www.sciencedirect.com/science/article/abs/pii/S1876107020303850
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/5998
ISSN: 1876-1070
Collection(s) :Publications Internationales

Fichier(s) constituant ce document :

Il n'y a pas de fichiers associés à ce document.

View Statistics

Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.

 

Valid XHTML 1.0! Ce site utilise l'application DSpace, Version 1.4.1 - Commentaires