Model for Determining the Probability of Congestion in a River Formation
Abstract
The available information on the values of the factors of congestion formation in the river bed makes it possible to assess the probability of its occurrence. Regression analysis of probability and factor values allows you to build a relationship between these values, but it is quite problematic to perform it using the usual methods of statistical processing due to the fact that the dependent variable is discrete, binary. The article presents an approach to assessing the likelihood of congestion from the point of view of classifying the facts of congestion and its absence depending on the values of the factors of congestion formation. As a result, a model was obtained for determining the probability of congestion in the riverbed, which is based on the method of logistic transformation.
About the Author
Yu. A. Tkachenko
Civil Defence Academy of Emercom of Russia
Russian Federation
Russian Federation
Yuliya A. Tkachenko
Sokolovskaya str., bld. 1А, Moscow region, Khimki,
md. Novogorsk, 141435
References
1. Tkachenko Yu.A. Analysis of the hydrometeorological factors of formation of conflicts on the rivers of the Tomsk region / Yu.A. Tkachenko, A.N. Tedurieva, E.E. Ostapchuk // Improving the Unified State System of Emergency Prevention and Response and Civil Defense of the Russian Federation at the present stage: Proceedings of Section No. 1 of the XXXIII International Scientific and Practical Conference, Khimki, March 01, 2022. Khimki: Academy of Civil Protection of the Ministry of the Russian Federation for Civil Defense, Emergencies and Elimination of Consequences of Natural Disasters, 2022. P. 101–105. (In Russ.)
2. Kozlov D.V., Kuleshov S.L. Multidimensional data analysis of jamming factors in river basins // Vodnye resursy. 2019;46(2):132–141. (In Russ.). https://doi.org/10.31857/S0321–0596462132–141]
3. Agafonova S.A., Berkovich K.M., Ruleva S.N. [et al.] Present-day specific features of the channel morphology and ice-jam formation at the Tom river // Water Sector of Russia: Problems, Technologies, Management. 2012;(6):21–33. (In Russ.)
4. Tkachenko Yu.A., Tkachenko P.N., Tedurieva A.N., Ivanov E.V. Analysis of scientific and methodological approaches to prediction of jam phenomena in the Tomsk region // Scientific and Educational Tasks of Civil Defence. 2022;(2):29–37. (In Russ.)
5. Tkachenko Yu.A., Tkachenko P.N., Ivanov E.V. On the approach to solving the problem of reducing the likelihood of congestion on the river section // Issues of Risk Analysis. 2024;21(1):56–64. (In Russ.)
6. Pampel F., Gruzdev A., Tsvirkun D. Logistic regression. M.: DMK Press, 2023. 218 p. (In Russ.)
7. Bogdanov L.Y. The evaluation of performance of binary classifiers based on logistic regression using ROC analysis // Bulletin of the Saratov State Technical University. 2010;4(2):92–97. (In Russ.)
Review
For citations:
Tkachenko Yu.A. Model for Determining the Probability of Congestion in a River Formation. Issues of Risk Analysis. 2024;21(3):42-49. (In Russ.)
Views:
112
Email this article 