Machine learning estimation of rock masses displacement

Описание

Тип публикации: статья из журнала

Год издания: 2024

Идентификатор DOI: 10.1051/e3sconf/202458301009

Аннотация: <jats:p>This paper presents a comprehensive analysis of the factors affecting landslide occurrence in Iran based on a dataset containing information on more than 4000 landslide cases. Both natural (slope, height, rainfall, distance to rivers and faults) and anthropogenic (type of land use) factors were studied. A random forest modeПоказать полностьюl was used to predict landslide risk and assess the significance of various factors. The results show that the most significant factors are terrain slope, elevation and distance to water bodies and tectonic faults. These findings can be used to develop preventive measures and improve landslide risk management strategies in the region.</jats:p>

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Издание

Журнал: E3S Web of Conferences

Выпуск журнала: Т. 583

Номера страниц: 01009

ISSN журнала: 25550403

Место издания: Les Ulis

Издатель: EDP Sciences - Web of Conferences

Персоны

  • Kukartsev V.V.
  • Kleshko I.I.
  • Dalisova N.A.
  • Khramkov V.V.

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