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Forecasting seismicactivity usingmachine learningalgorithms Kukartsev VladislavDegtyareva Ksenia2024 год

Forecasting seismic activity using machine learning algorithms
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: Forecasting seismic activity using machine learning algorithms : доклад, тезисы доклада / V. V. Kukartsev, K. K. Degtyareva. - [S. l. : s. n.], 2024. - Текст : непосредственный // E3S WEB OF CONFERENCES : International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2024) / International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2024) (2024 ; 15.10 - 18.10 ; Astana, Kazakhstan). - Les Ulis, 2024. - 592. - P. 05002. - DOI 10.1051/e3sconf/202459205002.
Аннотация: <jats:p>In this paper, the possibility of using the random forest method to predict earthquake locations based on historical data was studied. The aim of the work was to develop a model capable of accurately predicting the geographical coordinates of earthquakes in India and adjacent regions. The model showed high accuracy of predictions, which is confirmed by low values of the mean quadratic error (MSE) and high coefficients of determination (R<jats:sup>2</jats:sup>). Analysis of the results showed that the model successfully captures patterns in the data and is able to accurately predict earthquakes in regions with high seismic activity. At the same time, areas with deviations were identified, which highlights the need for further research to improve the model and increase its accuracy. This study demonstrates the promise of machine learning methods in seismological forecasting tasks and can serve as a basis for creating more accurate earthquake early warning systems.</jats:p>
Год издания: 2024
Авторы: Kukartsev Vladislav, Degtyareva Ksenia
Издательство: Les Ulis
Источник: E3S WEB OF CONFERENCES
Выпуск: 592
Мероприятие: International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2024) (Astana, Kazakhstan, 2024 ; 15.10 - 18.10)
Номера страниц: 05002
Количество экземпляров:
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