Machine learning based simulation of an anti-cancer drug (busulfan) solubility in supercritical carbon dioxide: ANFIS model and experimental validation-Reference-Cited by-同舟云学术

Machine learning based simulation of an anti-cancer drug (busulfan) solubility in supercritical carbon dioxide: ANFIS model and experimental validation

Published:2021-09 Issue: Volume:338 Page:116731
ISSN:0167-7322
Container-title:Journal of Molecular Liquids
language:en
Short-container-title:Journal of Molecular Liquids

Author:

Zhu Huimin,Zhu Liwei,Sun Zihong,Khan Afrasyab

Funder

Council on grants of the President of the Russian Federation

Publisher

Elsevier BV

Subject

Materials Chemistry,Physical and Theoretical Chemistry,Spectroscopy,Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference59 articles.

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4. Changes in the Number of Membership Functions for Predicting the Gas Volume Fraction in Two-Phase Flow Using Grid Partition Clustering of the ANFIS Method;Babanezhad;ACS Omega,2020

5. Computational Fluid Dynamics Simulation of Mass Transfer in the Separation of Fermentation Products Using Nanoporous Membranes;Ranjbar;Chem. Eng. Technol.,2013

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