Identification of water samples from different springs and rivers of Kharkiv: Comparison of methods for multivariate data analysis

The application of artificial neural networks for identifying water samples from different springs and rivers of Kharkiv based on the data about metal ions concentrations was studied. Using the river-water samples as an example, we demonstrated that the artificial neural networks enabled the correct identification of water samples, even if there were some gaps in the initial data. The procedure for determining the optimal number of neurons for synthesizing neural networks was proposed.