A neural network model for automated prediction of avalanche danger level

Sharma, Vipasana; Kumar, Sushil; Sushil, Rama

doi:https://doi.org/10.5194/nhess-23-2523-2023

Articles | Volume 23, issue 7

https://doi.org/10.5194/nhess-23-2523-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Natural hazards’ impact on natural and built heritage and...

https://doi.org/10.5194/nhess-23-2523-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 7

Research article

|

14 Jul 2023

Research article |

| 14 Jul 2023

A neural network model for automated prediction of avalanche danger level

Vipasana Sharma, Sushil Kumar, and Rama Sushil

Data sets

Weather, snowpack and danger ratings data for automated avalanche danger level predictions C. Pérez-Guillén, F. Techel, M. Hendrick, M. Volpi, A. van Herwijnen, T. Olevski, G. Obozinski, F. Pérez-Cruz, and J. Schweizer https://doi.org/10.16904/envidat.330

Model code and software

vipasanasharma/Automated-Prediction-of-Avalanches: First V. Sharma https://doi.org/10.5281/zenodo.8139913

Short summary

Snow avalanches are a natural hazard that can cause danger to human lives. This threat can be reduced by accurate prediction of the danger levels. The development of mathematical models based on past data and present conditions can help to improve the accuracy of prediction. This research aims to develop a neural-network-based model for correlating complex relationships between the meteorological variables and the profile variables.