As the tunnel excavation and resource exploitation go deeper into the Earth, increasing number of rockburst occur all over the world. However, the understanding of rockburst prediction and rockburst proneness evaluation is still at its infancy. In this paper, to accurately and efficiently predict rockburst proneness, a multi-index evaluation method for rockburst proneness of deep underground rock openings is established, verified and applied. The multi-index evaluation method is put forward based on attribute recognition model and combined weighting method. Eight discriminate indexes are taken into account, i.e., in-situ stress, rock brittleness, elastic deformation energy, maximum storage elastic strain energy, rock integrity, groundwater condition, section design size and site construction status. Through analyzing a variety of practical engineering cases, the weight values of each index are evaluated by combined method of analytic hierarchy process and random forest algorithm. It is found that the groundwater condition, in-situ stress, rock integrity and elastic deformation energy are the most important evaluation indexes. The attribute recognition model of rockburst proneness is established with weight evaluation and the attribute measure function of each index, where the attribute measure function is developed by analyzing the rockburst proneness of each index and setting up the standards for risk classes. The accuracy and applicability of the proposed multi-index evaluation method are verified through analyzing rockburst cases of twenty engineering projects. It is then applied to the rockburst hazard evaluation of the Caoguoshan Tunnel. Results showed that the predictions for rockburst proneness are consistent with the actual rockburst occurrence. The findings in this paper could facilitate evaluating of rockburst proneness for deep underground rock opening and be of great significance for rockburst risk prediction.

随着隧道开挖和资源开发深入地球，世界各地发生越来越多的岩爆。然而，对岩爆预测和岩爆倾向性评价的认识仍处于起步阶段。本文为准确、高效地预测岩爆倾向性，建立、验证并应用了深部地下岩石洞口岩爆倾向性的多指标评价方法。提出了基于属性识别模型和组合加权法的多指标评价方法。综合考虑地应力、岩石脆性、弹性变形能、最大储存弹性应变能、岩石完整性、地下水状况、断面设计尺寸和现场施工状态8个判别指标。通过对各种实际工程案例的分析，采用层次分析法和随机森林算法相结合的方法对各指标的权重值进行评价。发现地下水状况、地应力、岩石完整性和弹性变形能是最重要的评价指标。以权重评价和各指标的属性测度函数建立岩爆易发性属性识别模型，通过对各指标的岩爆易发性进行分析，建立风险等级标准，开发属性测度函数。通过对20个工程项目岩爆案例的分析，验证了所提出的多指标评价方法的准确性和适用性。并将其应用于草果山隧道岩爆危险性评价。结果表明，对岩爆倾向性的预测与实际的岩爆发生情况是一致的。本文研究结果有助于评价深部地下岩石开孔的岩爆倾向性，对岩爆风险预测具有重要意义。