A neural network model for automated prediction of avalanche danger level

IF 4.2 2区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Natural Hazards and Earth System Sciences Pub Date : 2023-07-14 DOI:10.5194/nhess-23-2523-2023

Vipasana Sharma, Sushil Kumar, R. Sushil

引用次数: 0

Abstract

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.

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雪崩危险度自动预测的神经网络模型

摘要雪崩对高海拔山区的人类生命和财产造成威胁。基于过去数据记录的数学模型可以预测危险程度。在本文中，我们提出了一个预测雪崩的神经网络模型。该模型使用瑞士阿尔卑斯山的质量控制子数据集进行管理。培训准确率79.75 % 验证准确度为76.54 % 已经实现。还对神经网络和随机森林模型的精度、召回率和F1等指标进行了比较分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Natural Hazards and Earth System Sciences 地学-地球科学综合

CiteScore

7.60

自引率

6.50%

发文量

192

审稿时长

3.8 months

期刊介绍： Natural Hazards and Earth System Sciences (NHESS) is an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences. Embracing a holistic Earth system science approach, NHESS serves a wide and diverse community of research scientists, practitioners, and decision makers concerned with detection of natural hazards, monitoring and modelling, vulnerability and risk assessment, and the design and implementation of mitigation and adaptation strategies, including economical, societal, and educational aspects.