Kohonen Self-Organizing Maps as a New Method for Determination of Salt Composition of Multi-Component Solutions
The paper presents the results of clusterization by
Kohonen self-organizing maps (SOM) applied for analysis of array of
Raman spectra of multi-component solutions of inorganic salts, for
determination of types of salts present in the solution. It is
demonstrated that use of SOM is a promising method for solution of
clusterization and classification problems in spectroscopy of multicomponent
objects, as attributing a pattern to some cluster may be
used for recognition of component composition of the object.
[1] T. R. Crompton, Determination of anions in natural and treated waters.
Taylor&Francis, 2002, 828 p.
[2] R. Michalski, "Ion Chromatography as a Reference Method for the
Determination of Inorganic Ions in Water and Wastewater,” Critical
Reviews in Analytical Chemistry, vol. 36, pp. 107–127, 2006.
[3] M. Chaplin, Water Structure and Behavior. www.lsbu.ac.uk/water, 2008
[4] T. A. Gogolinskaia, S. V. Patsaeva, and V. V. Fadeev, "About
regularities of change of band 3100-3700 cm-1 of water Raman
spectrum of water solutions of salts,” DAN USSR (Russian), vol. 290,
no. 5, pp. 1099-1103, 1986.
[5] W. W. Rudolph, and G. Irmer, "Raman and infrared spectroscopic
investigation on aqueous alkali metal phosphate solutions and density
functional theory calculations of phosphate-water clusters,” Applied
Spectroscopy, vol. 61, no. 12, pp. 274A-292A, Dec. 2007.
[6] A. N. Gorban, V. L. Dunin-Barkovsky et.al., "Neural-network
informational models of complex engineering systems” in
Neuroinformatica, ch. 4, S.A. Terechov, Ed. Novosibirsk: Nauka.
Sibirskoe predpriyatie RAN, 1998.
[7] S. A. Dolenko, T. A. Dolenko, I. G. Persiantsev, V. V. Fadeev, and S. A.
Burikov, "Solution of inverse problems of optical spectroscopy using
neural networks,” Neurocomputers: Development, Application, no. 1-2,
pp. 89-97, 2005. (Russian)
[8] S. A. Burikov, T. A. Dolenko, and V. V. Fadeev, "Identification of
Inorganic Salts and Determination of Their Concentrations in Water
Solutions from the Raman Valence Band Using Artificial Neural
Networks,” Pattern Recognition and Image Analysis, vol. 17, no. 4,
pp. 554-559, 2007.
[9] S. A. Burikov, S. A. Dolenko et al., "Application of Artificial Neural
Networks to Solve Problems of Identification and Determination of
Concentration of Salts in Multi-Component Water Solutions by Raman
spectra,” Optical Memory and Neural Networks (Information Optics),
vol. 19, no. 2, pp. 140-148, 2010.
[10] S. A. Dolenko, S. A. Burikov, T. A. Dolenko and I.G. Persiantsev,
"Adaptive Methods for Solving Inverse Problems in Laser Raman
Spectroscopy of Multi-Component Solutions,” Pattern Recognition and
Image Analysis, vol. 22, no. 4, pp. 551-558, 2012.
[11] T. Kohonen, Self-Organizing Maps. 3d Edition. Berlin: Springer, 2001.
[12] U. Seiffert, and L.C. Jain, Self-Organizing neural networks: recent
advances and applications, Heidelberg, New York: Physica-Verlag,
2002.
[13] "Self-Organizing Maps - Applications and Novel Algorithm Design,”
2011. http://www.intechopen.com/books/self-organizing-mapsapplications-
and-novel-algorithm-design
[14] Loginom – analytical platform. http://loginom.basegroup.ru/
[15] S. A. Dolenko, S. A. Burikov, T. A. Dolenko, A. O. Efitorov, and I. G.
Persiantsev, "Input data compression at neural-network solution of
inverse problems of spectroscopy of multicomponent solutions,” in Proc.
XV Russian Scientific-Technical Conf. Neuroinformatica (Russian).
Moscow, 2013, vol. 2, pp. 205-215.
[16] B. Desgraupes. Clustring Indices. Supplement for Package clusterCrit
for R. http://cran.r-project.org/web/packages/clusterCrit/vignettes/
clusterCrit.pdf
[1] T. R. Crompton, Determination of anions in natural and treated waters.
Taylor&Francis, 2002, 828 p.
[2] R. Michalski, "Ion Chromatography as a Reference Method for the
Determination of Inorganic Ions in Water and Wastewater,” Critical
Reviews in Analytical Chemistry, vol. 36, pp. 107–127, 2006.
[3] M. Chaplin, Water Structure and Behavior. www.lsbu.ac.uk/water, 2008
[4] T. A. Gogolinskaia, S. V. Patsaeva, and V. V. Fadeev, "About
regularities of change of band 3100-3700 cm-1 of water Raman
spectrum of water solutions of salts,” DAN USSR (Russian), vol. 290,
no. 5, pp. 1099-1103, 1986.
[5] W. W. Rudolph, and G. Irmer, "Raman and infrared spectroscopic
investigation on aqueous alkali metal phosphate solutions and density
functional theory calculations of phosphate-water clusters,” Applied
Spectroscopy, vol. 61, no. 12, pp. 274A-292A, Dec. 2007.
[6] A. N. Gorban, V. L. Dunin-Barkovsky et.al., "Neural-network
informational models of complex engineering systems” in
Neuroinformatica, ch. 4, S.A. Terechov, Ed. Novosibirsk: Nauka.
Sibirskoe predpriyatie RAN, 1998.
[7] S. A. Dolenko, T. A. Dolenko, I. G. Persiantsev, V. V. Fadeev, and S. A.
Burikov, "Solution of inverse problems of optical spectroscopy using
neural networks,” Neurocomputers: Development, Application, no. 1-2,
pp. 89-97, 2005. (Russian)
[8] S. A. Burikov, T. A. Dolenko, and V. V. Fadeev, "Identification of
Inorganic Salts and Determination of Their Concentrations in Water
Solutions from the Raman Valence Band Using Artificial Neural
Networks,” Pattern Recognition and Image Analysis, vol. 17, no. 4,
pp. 554-559, 2007.
[9] S. A. Burikov, S. A. Dolenko et al., "Application of Artificial Neural
Networks to Solve Problems of Identification and Determination of
Concentration of Salts in Multi-Component Water Solutions by Raman
spectra,” Optical Memory and Neural Networks (Information Optics),
vol. 19, no. 2, pp. 140-148, 2010.
[10] S. A. Dolenko, S. A. Burikov, T. A. Dolenko and I.G. Persiantsev,
"Adaptive Methods for Solving Inverse Problems in Laser Raman
Spectroscopy of Multi-Component Solutions,” Pattern Recognition and
Image Analysis, vol. 22, no. 4, pp. 551-558, 2012.
[11] T. Kohonen, Self-Organizing Maps. 3d Edition. Berlin: Springer, 2001.
[12] U. Seiffert, and L.C. Jain, Self-Organizing neural networks: recent
advances and applications, Heidelberg, New York: Physica-Verlag,
2002.
[13] "Self-Organizing Maps - Applications and Novel Algorithm Design,”
2011. http://www.intechopen.com/books/self-organizing-mapsapplications-
and-novel-algorithm-design
[14] Loginom – analytical platform. http://loginom.basegroup.ru/
[15] S. A. Dolenko, S. A. Burikov, T. A. Dolenko, A. O. Efitorov, and I. G.
Persiantsev, "Input data compression at neural-network solution of
inverse problems of spectroscopy of multicomponent solutions,” in Proc.
XV Russian Scientific-Technical Conf. Neuroinformatica (Russian).
Moscow, 2013, vol. 2, pp. 205-215.
[16] B. Desgraupes. Clustring Indices. Supplement for Package clusterCrit
for R. http://cran.r-project.org/web/packages/clusterCrit/vignettes/
clusterCrit.pdf
@article{"International Journal of Chemical, Materials and Biomolecular Sciences:68141", author = "Sergey A. Burikov and Tatiana A. Dolenko and Kirill A. Gushchin and Sergey A. Dolenko", title = "Kohonen Self-Organizing Maps as a New Method for Determination of Salt Composition of Multi-Component Solutions", abstract = "The paper presents the results of clusterization by
Kohonen self-organizing maps (SOM) applied for analysis of array of
Raman spectra of multi-component solutions of inorganic salts, for
determination of types of salts present in the solution. It is
demonstrated that use of SOM is a promising method for solution of
clusterization and classification problems in spectroscopy of multicomponent
objects, as attributing a pattern to some cluster may be
used for recognition of component composition of the object.
", keywords = "Kohonen self-organizing maps, clusterization, multicomponent
solutions, Raman spectroscopy.", volume = "8", number = "10", pages = "1146-5", }
