Comparison the capability of artificial neural network (ANN) and EOS for prediction of solid solubilities in supercritical carbon dioxide
Author:
Publisher
Elsevier BV
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy,General Chemical Engineering
Reference68 articles.
1. Neural networks: A new method for solving chemical problems or just a passing phase?
2. Development of a generalized neural network
3. Solubility prediction of anthracene in binary and ternary solvents by artificial neural networks (ANNs)
4. Comparison between neural network and mathematical modeling of supercritical CO2 extraction of black pepper essential oil
5. Modeling of solid–supercritical fluid phase equilibria with a cubic equation of state—Gex model
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