Geodesic
Construction of Kohonen self-organizing map (SOM) for prediction of mudflow types
News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 5, pp. 129-137.

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The paper describes a self-organizing Kohonen map (SOM) that analyzes the mudflow type. SOM is trained on real cadastre data of mudflow danger in the south of the European part of Russia. The purpose of the work is to obtain forecasts of mudflow types. The results of the work show that SOM provides good accuracy in predicting mudflow types. The main task will be to cluster data related to geological and meteorological factors in order to identify patterns that can be used to predict the risk of occurrence of various mudflow types. It is expected that the results of this work will contribute to more accurate and on time forecasting of mudflows, which, in turn, will help minimize damage from these natural phenomena.
Keywords: data clustering, SOM clustering method, SOM model, Kohonen self-organizing maps, mudflow type classification 
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R. A. Zhilov. Construction of Kohonen self-organizing map (SOM) for prediction of mudflow types. News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 5, pp. 129-137. http://geodesic.mathdoc.fr/item/IZKAB_2024_26_5_a9/

[1] V. V. Khvorostov, I. I. Khvorostov, “Extraordinary and ultra-seismic flows in the territory of the Greater Caucasus”, Proceedings of the international conference “Sustainable Development of Mountain Territories”, 2004, 605 (In Russian)

[2] N. V. Kondratyeva, A. Kh. Adzhiev, M. Yu. Bekkiev et al., Inventory of mudflow danger in the south of the European part of Russia, Pechatnuy dvor, Nalchik, 2015, 148 pp. (In Russian)

[3] N. V. Kondratieva, “Preliminary assessment of the maximum volume of solid mudflow deposits using mathematical statistics methods for the Central Caucasus”, Modern problems of science and education, 2014, no. 4, 50–56 (In Russian)

[4] T. Kohonen, Self-Organizing Maps (Third Extended Edition), New York, 2001, 501 pp. | MR

[5] R. A. Zhilov, “Application of neural networks in data clustering”, News of the Kabardino Balkarian Scientific Center of RAS, 2021, no. 1 (99), 15–19 (In Russian) | DOI

[6] N. A. Radeev, “Prediction of avalanche danger using machine learning methods”, NSU Bulletin Information Technologies, 19:2 (2021), 92–101, Series (In Russian) | DOI

[7] P. Flakh, Machine learning: the science and art of building algorithms that extract knowledge from data, DMK Press, Moscow, 2015, 400 pp. (In Russian)