Predicting solubility in supercritical fluid extraction using a neural network

Battersby, Paul, Dean, John, Tomlinson, William, Hitchen, Steven and Myers, Peter (1994) Predicting solubility in supercritical fluid extraction using a neural network. Analyst, 119 (5). pp. 925-928. ISSN 0003-2654

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Official URL: http://dx.doi.org/10.1039/AN9941900925

Abstract

A neural network has been constructed for prediction of the solubility of analytes in supercritical carbon dioxide. Preliminary studies for the input of molecular structure into the network indicates that connectivity indices are adequate to provide structural information in a condensed form. This allows neural networks, which would otherwise be very extensive, to have reduced training times; it also reduces the possibility of memorization of the training data and over-training of the network.

Item Type: Article
Uncontrolled Keywords: Supercritical fluid extraction; solubility prediction; neural networks; connectivity indices
Subjects: F100 Chemistry
G400 Computer Science
G500 Information Systems
Department: Faculties > Health and Life Sciences > School of Life Sciences > Applied Sciences
Depositing User: Becky Skoyles
Date Deposited: 05 Feb 2015 11:46
Last Modified: 04 Mar 2016 15:47
URI: http://nrl.northumbria.ac.uk/id/eprint/19573

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