Abstract
The studied inverse problem is determination of partial concentrations of inorganic salts in multi-component water solutions by their Raman spectra. The problem is naturally divided into two parts: 1) determination of the component composition of the solution, i.e. which salts are present and which not; 2) determination of the partial concentration of each of the salts present in the solution. Within the first approach, both parts of the problem are solved simultaneously, with a single neural network (perceptron) with several outputs, each of them estimating the concentration of the corresponding salt. The second approach uses data clusterization by Kohonen networks for consequent identification of component composition of the solution by the cluster, which the spectrum of this solution falls into. Both approaches and their results are discussed in this paper.
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Dolenko, S., Burikov, S., Dolenko, T., Efitorov, A., Gushchin, K., Persiantsev, I. (2014). Neural Network Approaches to Solution of the Inverse Problem of Identification and Determination of Partial Concentrations of Salts in Multi-сomponent Water Solutions. In: Wermter, S., et al. Artificial Neural Networks and Machine Learning – ICANN 2014. ICANN 2014. Lecture Notes in Computer Science, vol 8681. Springer, Cham. https://doi.org/10.1007/978-3-319-11179-7_101
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DOI: https://doi.org/10.1007/978-3-319-11179-7_101
Publisher Name: Springer, Cham
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