Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms
Waddell, R.J.H. and Nic Daeid, N. and Littlejohn, D. (2004) Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms. Analyst, 129. pp. 235-240. ISSN 0003-2654
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Abstract
This work is concerned with an investigation into the practicalities of using ICP-MS data obtained from the analysis of ecstasy tablets to provide linkage information from seizure to seizure. The generated data was analysed using different statistical techniques, namely principal component analysis, Hierarchical clustering and artificial neural networks. The relative merits of these different techniques are discussed.
Creators(s): |
Waddell, R.J.H., Nic Daeid, N. and Littlejohn, D. ![]() | Item type: | Article |
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ID code: | 38265 |
Keywords: | ICP-MS, ecstacy, seizure, principal component analysis, Hierarchical clustering, Chemistry, Biochemistry, Spectroscopy, Environmental Chemistry, Analytical Chemistry, Electrochemistry |
Subjects: | Science > Chemistry |
Department: | Faculty of Science > Pure and Applied Chemistry |
Depositing user: | Pure Administrator |
Date deposited: | 07 Mar 2012 11:47 |
Last modified: | 01 Jan 2021 08:45 |
URI: | https://strathprints.strath.ac.uk/id/eprint/38265 |
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