Solubility prediction of anthracene in binary and ternary solvents by artificial neural networks (ANNs)-Reference-Cited by-同舟云学术

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Solubility prediction of anthracene in binary and ternary solvents by artificial neural networks (ANNs)

Published:2004-11 Issue: Volume:225 Page:133-139
ISSN:0378-3812
Container-title:Fluid Phase Equilibria
language:en
Short-container-title:Fluid Phase Equilibria

Author:

Jouyban Abolghasem,Majidi Mir-Reza,Jabbaribar Farnaz,Asadpour-Zeynali Karim

Publisher

Elsevier BV

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy,General Chemical Engineering

Reference30 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 Mixed Solvents Using a Minimum Number of Experimental Data.

4. Models to Predict Solubility in Ternary Solvents Based on Sub-binary Experimental Data.

5. Solubility Prediction for Furosemide in Water-Cosolvent Mixtures Using the Minimum Number of Experiments

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1. Data-Driven Point Adjusted Jouyban-Acree-Artificial Neural Network Hybrid Model for Predicting Solubility of Active Pharmaceutical Ingredients in Binary Solvent Mixtures;Industrial & Engineering Chemistry Research;2024-09-11

2. Artificial Neural Network;Applications of Nature-Inspired Computing in Renewable Energy Systems;2022

3. Prediction of CO₂ Mass Transfer Flux in Aqueous Amine Solutions Using Artificial Neural Networks;IRAN J CHEM CHEM ENG;2020

4. Comparing the capability of artificial neural network (ANN) and CSMHYD program for predicting of hydrate formation pressure in binary mixtures;Journal of Petroleum Science and Engineering;2015-12

5. Application of neural network molecular modeling for correlating and predicting Henry's law constants of gases in [bmim][PF6] at low pressures;Fluid Phase Equilibria;2012-10

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