Preprints
https://doi.org/10.5194/egusphere-2023-701
https://doi.org/10.5194/egusphere-2023-701
17 Apr 2023
 | 17 Apr 2023

Neural Network Model for Automated Prediction of Avalanche Danger Level

Vipasana Sharma, Sushil Kumar, and Rama Sushil

Abstract. Snow avalanches cause danger to human lives and property worldwide in high-altitude mountainous regions. Mathematical models based on past data records can predict the danger level. In this paper, we are proposing a neural network model for predicting avalanches. The model is trained with a quality-controlled sub-dataset of Swiss Alps. Training accuracy of 79.75 % and validation accuracy of 76.54 % have been achieved. Comparative analysis of neural network and random forest models concerning metrics like precision, recall, and F1 has also been carried out.

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Journal article(s) based on this preprint

14 Jul 2023
A neural network model for automated prediction of avalanche danger level
Vipasana Sharma, Sushil Kumar, and Rama Sushil
Nat. Hazards Earth Syst. Sci., 23, 2523–2530, https://doi.org/10.5194/nhess-23-2523-2023,https://doi.org/10.5194/nhess-23-2523-2023, 2023
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
Snow avalanches are a natural hazard that can cause danger to human lives. This threat can be...
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