Comprehensive Analysis of Mudflow Data Using Machine Learning Methods

Maryana Gedueva; Elena Kyul; L. A. Lyutikova; Elena Korchagina; Z. S. Nirova

doi:10.2205/2025ES001072

UDC

CSCSTI

37.00 38.00

Russian Classification of Professions by Education

05.00.00

Russian Trade and Bibliographic Classification

Russian Library and Bibliographic Classification

BISAC

SCI

VAK Russia

1.6

COMPREHENSIVE ANALYSIS OF MUDFLOW DATA USING MACHINE LEARNING METHODS Comprehensive Analysis of Mudflow Data Using Machine Learning Methods

АА Аа

Published in Russian Journal of Earth Sciences · ELocator: ES6003 · Rubric: Special Issue: “Advances in Environmental Studies, from the VIII International Scientific and Practical Conference ‘Fundamental and Applied Aspects of Geology, Geophysics and Geoecology Using Modern Information Technologies’ ”

DOI: https://doi.org/10.2205/2025ES001072 · EDN: RTNMVL

Received: 10.09.2025 Accepted: 10.11.2025 Published: 10.12.2025 Language of publication: ENG

Authors

Maryana Gedueva

ORCID

Elena Kyul

ORCID

L. A. Lyutikova

ORCID

Elena Korchagina

ORCID

Z. S. Nirova

Maryana Gedueva

Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences Russian Federation · Nalchik

ORCID

Elena Kyul

Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences Russian Federation · Nalchik

ORCID

L. A. Lyutikova

Institute of Applied Mathematics and Automation, KBSC RAS Russian Federation

ORCID

Elena Korchagina

Federal Scientific Center "Kabardino-Balkarian Scientific Center of the RAS" Russian Federation · Nalchik

ORCID

Z. S. Nirova

Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences Russian Federation

ABSTRACT

The paper presents a comprehensive analysis of mudflow basin parameters, conducted using machine learning methods. For the northern slope of the Greater Caucasus, data on the main parameters of mudflow basins were analyzed to build models that allow forecasting mudflows with certain characteristics. A set of machine learning methods was used (clustering, search for association rules, logistic regression, etc.). Key factors of mudflows were identified, models were developed for classifying mudflow types and predicting the volume of one-time removal of material, and a number of association rules with high reliability were identified that describe the relationships between factors influencing mudflow processes. The obtained results show great potential in the application of learning in the tasks of analysis and forecasting of mudflow processes. Ultimately, this will allow, based on the addition of mudflow data and updating of existing mudflow maps, to develop more effective measures to reduce the impact of mudflows on the environment to a minimum.

KEYWORDS

Mudflow, mudflow basin, mudflow activity, mudflow formation factors, machine learning methods, analysis models, clustering, multiparameter regression, association discretization rules

Funding

The work was carried out within the framework of the state assignment of KBSC RAS.

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Chief Editor

Alexei Gvishiani

rjes@wdcb.ru

Deputy Chief Editor

Boris Dzeboev

rjes@wdcb.ru

Managing Editor

Ernest Kedrov

rjes@wdcb.ru

Responsible Secretary

Natalya Kareva

rjes@wdcb.ru

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GOST

Gedueva M. M., Kyul E. V., Lyutikova L. A., Korchagina E. A., Nirova Z. S. Comprehensive Analysis of Mudflow Data Using Machine Learning Methods // Russian Journal of Earth Sciences. 2025. no. 6. ES6003. DOI: https://doi.org/10.2205/2025ES001072. EDN: RTNMVL. (Date of access 07.09.2026).

MLA

Maryana Gedueva, Kyul E. V., Lyutikova L. A., Korchagina E. A., Nirova Z. S.. "Comprehensive Analysis of Mudflow Data Using Machine Learning Methods." Russian Journal of Earth Sciences 25.6 (2025): ES6003. DOI: https://doi.org/10.2205/2025ES001072. EDN: RTNMVL.

APA

Gedueva M. M., Kyul E. V., Lyutikova L. A., Korchagina E. A., Nirova Z. S. (2025). Comprehensive Analysis of Mudflow Data Using Machine Learning Methods. Russian Journal of Earth Sciences, 25(6), ES6003. https://doi.org/10.2205/2025ES001072 EDN: RTNMVL.

Chicago

Maryana Gedueva, Kyul E. V., Lyutikova L. A., Korchagina E. A., Nirova Z. S.. "Comprehensive Analysis of Mudflow Data Using Machine Learning Methods." Russian Journal of Earth Sciences 25, no. 6 (2025): ES6003. https://doi.org/10.2205/2025ES001072. EDN: RTNMVL.

WIKI

{{cite journal | author = Gedueva M. M., Kyul E. V., Lyutikova L. A., Korchagina E. A., Nirova Z. S. | title = Comprehensive Analysis of Mudflow Data Using Machine Learning Methods | journal = Russian Journal of Earth Sciences | year = 2025 | volume = 25 | issue = 6 | pages = ES6003 | doi = 10.2205/2025ES001072 }} EDN: RTNMVL

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COMPREHENSIVE ANALYSIS OF MUDFLOW DATA USING MACHINE LEARNING METHODS Comprehensive Analysis of Mudflow Data Using Machine Learning Methods

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