基于机器学习的区域滑坡危险性评价方法综述

我国滑坡灾害分布范围广，危害严重。区域滑坡危险性评价一直都是滑坡灾害防灾减灾的重要内容之一。近年来，随着大数据和人工智能技术的飞速发展，机器学习技术逐渐在滑坡灾害危险性评价方面得到广泛应用，并取得了较好效果。在大量研读文献的基础上，系统阐述了基于机器学习技术的滑坡危险性评价方法研究现状。综述从评价因子选择与量化归一化、数据清洗与样本集构建、模型选取与训练评价等三个关键环节对现有研究成果进行分析评述，最后对机器学习滑坡危险性评价方法的发展趋势提出讨论意见。

A review of the methods of regional landslide hazard assessment based on machine learning

The landslide disaster in China is widespread and serious. Regional landslide risk assessment has always been one of the most important contents of landslide disaster prevention and mitigation. In recent years, with the rapid development of big data and artificial intelligence technology, machine learning technology has gradually been widely used in landslide hazard assessment andachieved good results. Based on a large number of literatures, this paper systematically expounds the research status of landslide risk assessment methods based on machine learning technology. This paper reviews and analyzes the existing research results from three key links: evaluation factor selection and quantization normalization, data cleaning and sample set construction, model selection and training evaluation, and finally puts forward some suggestions on the development trend of machine learning landslide risk evaluation methods.