Towards an expert system for enantioseparations: induction of rules using machine learning
Bryant, CH, Adam, AE, Taylor, DR and Rowe, RC 1996, 'Towards an expert system for enantioseparations: induction of rules using machine learning' , Chemometrics and Intelligent Laboratory Systems, 34 (1) , pp. 21-40.
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A commercially available machine induction tool was used in an attempt to automate the acquisition of the knowledge needed for an expert system for enantioseparations by High Performance Liquid Chromatography using Pirkle-type chiral stationary phases (CSPs). Various rule-sets were induced that recommended particular CSP chiral selectors based on the structural features of an enantiomer pair. The results suggest that the accuracy of the optimal rule-set is 63% + or - 3% which is more than ten times greater than the accuracy that would have resulted from a random choice.
|Uncontrolled Keywords:||expert systems, enantioseparations, machine learning|
|Themes:||Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Subjects / Themes > Q Science > QD Chemistry
Subjects outside of the University Themes
|Schools:||Schools > School of Computing, Science and Engineering
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)
|Journal or Publication Title:||Chemometrics and Intelligent Laboratory Systems|
|Depositing User:||Dr Chris H. Bryant|
|Date Deposited:||17 Feb 2009 15:25|
|Last Modified:||01 Dec 2015 00:04|
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