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This study considers a neural network solution to the inverse problem based on the integration of optical spectroscopy methods for determining ion concentrations in aqueous solutions. The effect of integration of physical methods is studied using the selection of significant input features. The previously formulated thesis is confirmed that if the integrated methods differ much by their accuracy, then the integration of these methods is ineffective.