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Ya. N. Pushkarova, A. B. Sledzevskaya, A. V. Panteleimonov, N. P. Titova, O. I. Yurchenko, V. V. Ivanov, Yu. V. Kholin

Identification of water samples from different SPRINGS and rivers of Kharkiv: comparison of methods of multivariate data analysis


Application of artificial neural networks for identification of water samples from different Kharkiv springs and rivers (Eastern Ukraine) was studied. The initial experimental data consisted of metal ions concentrations in the water samples. The artificial neural networks algorithms were demonstrated to provide the correct identification of water samples even in the presence of gaps in the initial data. To realize successfully each particular neural network it is necessary to determine the optimal number of neurons. The corresponding rule was proposed.
Key words: qualitative chemical analysis, identification, artificial neural network, linear discriminant analysis.
Moscow University Chemistry Bulletin.
2012, Vol. 53, No. 6, P. 405

Copyright (C) Chemistry Dept., Moscow State University, 2002
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