Ya. N. Pushkarova, A. B. Sledzevskaya, A. V. Panteleimonov, N. P. Titova, O. I. Yurchenko, V. V. Ivanov, Yu. V. Kholin
of water samples from different SPRINGS and rivers of Kharkiv: comparison of
methods of multivariate data analysis
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
Key words: qualitative chemical analysis, identification, artificial neural
network, linear discriminant analysis.
Copyright (C) Chemistry Dept., Moscow State University, 2002