露天矿山地表变形预测及灾害风险评价的研究对提高灾害预警准确性及制定安全防治措施具有重要意义。近年来，大数据、云计算、人工智能方法的发展，为传统矿山的智能化转型提供了技术支持。从矿山地表变形智能感知、预测及灾害风险评价3个方面概述了露天矿山地表变形灾害的研究进展；梳理了矿山地表变形智能监测技术，选择智能监测手段需要从数据精度、安装成本、后处理速度等多角度权衡；从传统变形预测方法与智能优化方法的结合、机器学习、深度学习3个方面总结了地表变形预测的智能建模方法；概述了矿山变形灾害典型风险评价方法的思路。基于当前研究进展，探讨了存在的问题及未来发展趋势，助力矿山灾害防治的智能升级。

Research on the prediction and disaster risk assessment of surface deformation in open-pit mines serves to improve the accuracy of disaster warning and make safety control decisions. In recent years, the development of big data, cloud computing and artificial intelligence methods has provided technical support for the intelligent transformation of traditional mines. This paper summarizes the research progress of surface deformation hazards in open-pit mines from three aspects: intelligent perception, intelligent prediction and disaster risk evaluation of surface deformation. Specifically, by reviewing the intelligent monitoring technologies of mine surface deformation, this study indicates that the choice of intelligent monitoring methods should factor in data accuracy, installation cost and post-processing speed, reviews the intelligent modeling methods of surface deformation prediction regarding the methodological combination of traditional deformation prediction and intelligent optimization, machine learning and deep learning, and summarizes the mechanism behind the typical risk assessment method of mine deformation hazards. Based on the current research progress, we discuss the existing research gap and prospects of intelligent prediction and disaster risk assessment of surface deformation in open-pit mines so as to offer reference to the intelligent upgrading of mine disaster prevention and control.