Solution of an inverse problem in raman spectroscopy of multi-component solutions of inorganic salts by artificial neural networks

Alexander Efitorov; Tatiana Dolenko; Sergey Burikov; Kirill Laptinskiy; Sergey Dolenko

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Solution of an inverse problem in raman spectroscopy of multi-component solutions of inorganic salts by artificial neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2016) 9887 LNCS 355-362

DOI: 10.1007/978-3-319-44781-0_42

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Abstract

The paper presents a study of aspects of using single and multiple output artificial neural networks to determine concentrations of inorganic salts in multicomponent water solutions by processing their Raman spectra. The dependence of the results on complexity of the inverse problem has been demonstrated. The results are compared for two data arrays including spectra of solutions of: (1) 5 salts composed of 10 different ions, and (2) 10 salts composed of 10 different ions.

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Efitorov, A., Dolenko, T., Burikov, S., Laptinskiy, K., & Dolenko, S. (2016). Solution of an inverse problem in raman spectroscopy of multi-component solutions of inorganic salts by artificial neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9887 LNCS, pp. 355–362). Springer Verlag. https://doi.org/10.1007/978-3-319-44781-0_42

Solution of an inverse problem in raman spectroscopy of multi-component solutions of inorganic salts by artificial neural networks

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