Predicting solubility in supercritical fluid extraction using a neural network

Paul Battersby, John Dean, William Tomlinson, Steven Hitchen, Peter Myers

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)925-928
Issue number5
Publication statusPublished - 1994


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