Predicting solubility in supercritical fluid extraction using a neural network-Reference-Cited by-同舟云学术

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Predicting solubility in supercritical fluid extraction using a neural network

Published:1994 Issue:5 Volume:119 Page:925
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Battersby P.,Dean J. R.,Tomlinson W. R.,Hitchen S. M.,Myers P.

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/1994/AN/AN9941900925

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust modelling of solubility in supercritical carbon dioxide using Bayesian methods;Journal of Molecular Graphics and Modelling;2010-04

2. Solubility prediction of 21 azo dyes in supercritical carbon dioxide using wavelet neural network;Dyes and Pigments;2007-01

3. Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide;Journal of Molecular Graphics and Modelling;2006-09

4. Application of Molecular Connectivity Indices to the Design of Supercritical Carbon Dioxide‐Soluble Metal Ion Extractants: SC‐CO2Solubilities of Symmetrically Substituted Alkylenediphosphonic Acids;Separation Science and Technology;2005-01-02

5. Prediction of solubility for polycyclic aromatic hydrocarbons in supercritical carbon dioxide using wavelet neural networks in quantitative structure property relationship;The Journal of Supercritical Fluids;2004-12

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