A neural network model for automated prediction of avalanche danger level

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 the 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.