[1] 冯夏庭, 肖亚勋, 丰光亮, 等. 岩爆孕育过程研究[J].岩石力学与工程学报, 2019, 38(4):649-673. (Feng Xiating, Xiao Yaxun, Feng Guangliang, et al. Study on the development process of rockbursts[J]. Chinese Journal of Rock Mechanics and Engineering, 2019, 38(4): 649-673. (in Chinese))
[2] Xue Y G, Li Z Q, Li S C, et al. Prediction of rock burst in underground caverns based on rough set and extensible comprehensive evaluation[J]. Bulletin of Engineering Geology and the Environment, 2019, 78(1):417- 429.
[3] 冯夏庭, 陈炳瑞, 明华军, 等. 深埋隧洞岩爆孕育规律与机制: 即时型岩爆[J]. 岩石力学与工程学报, 2012, 31(3): 433-444. (Feng Xiating, Chen Bingrui, Ming Huajun, et al. Evolution law and mechanism of rockbursts in deep tunnels: Immediate rockburst[J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(3): 433-444. (in Chinese))
[4] 谢学斌, 李德玄, 孔令燕, 等. 基于CRITIC-XGB算法的岩爆倾向等级预测模型[J]. 岩石力学与工程学报, 2020, 39(10): 1975-1982. (Xie Xuebin, Li Dexuan, Kong Lingyan, et al. Rockburst propensity prediction model based on CRITIC-XGB algorithm[J]. Chinese Journal of Rock Mechanics and Engineering, 2020, 39(10): 1975-1982. (in Chinese))
[5] 王元汉, 李卧东, 李启光, 等. 岩爆预测的模糊数学综合评判方法[J]. 岩石力学与工程学报, 1998, 17(5): 493-501. (Wang Yuanhan, Li Wodong, Li Qiguang, et al. Method of fuzzy comprehensive evaluations for rockburst prediction[J]. Chinese Journal of Rock Mechanics and Engineering, 1998, 17(5): 493-501. (in Chinese))
[6] 徐士良, 朱合华. 公路隧道通风竖井岩爆机制颗粒流模拟研究[J]. 岩土力学, 2011, 32(3): 885- 890.(Xu Shiliang, Zhu Hehua. Particle flow simulation of rock burst mechanism for highway tunnel ventilation shaft[J]. Rock and Soil Mechanics, 2011, 32(3): 885- 890. (in Chinese))
[7] 李康楠, 吴雅琴, 杜锋, 等. 基于卷积神经网络的岩爆烈度等级预测[J]. 煤田地质与勘探, 2023, 51(10): 94-103. (Li Kangnan, Wu Yaqin, Du Feng, et al. Prediction of rockburst intensity grade based on convolutional neural network[J]. Coal Geology & Exploration. 2023, 51(10): 94-103. (in Chinese))
[8] 曲宏略, 刘哲言, 杨龙等. 基于应力判据的隧道岩爆预测评估研究[J]. 地下空间与工程学报, 2020, 16 (增2): 934-938, 956. (Qu Honglue, Liu Zheyan, Yang Long, et al. Prediction and evaluation of rock burst in tunnel based on stress criterion[J]. Chinese Journal of Underground Space and Engineering, 2020, 16(Supp.2): 934-938, 956. (in Chinese))
[9] 孙飞跃, 刘希亮, 郭佳奇, 等. 岩爆预测评估方法的动力数值分析[J]. 应用力学学报, 2022, 39(1): 26-34.(Sun Feiyue, Liu Xiliang, Guo Jiaqi, et al. Dynamic numerical calculation analysis of rockburst prediction assessment methods[J]. Chinese Journal of Applied Mechanics, 2022, 39(1): 26-34. (in Chinese))
[10] Jiang L S, Kong P, Zhang P P, et al. Dynamic analysis of the rock burst potential of a longwall panel intersecting with a fault[J]. Rock Mechanics and Rock Engineering, 2020, 53(4): 1737- 1754.
[11] Yang Z Q, Liu C, Zhu H Z, et al. Mechanism of rock burst caused by fracture of key strata during irregular working face mining and its prevention methods[J]. International Journal of Mining Science and Technology, 2019, 29(6):889-897.
[12] Dong L J, Li X B, Peng K. Prediction of rockburst classification using random forest[J]. Transactions of Nonferrous Metals Society of China, 2013, 23(2): 472-477.
[13] Lin Y, Zhou K P, Li J L, Application of cloud model in rock burst prediction and performance comparison with three machine learnings algorithms[J]. IEEE Access, 2018(6):30958-30968.
[14] 王迎超, 尚岳全, 孙红月, 等. 基于功效系数法的岩爆烈度分级预测研究[J]. 岩土力学, 2010, 31(2): 529-534.(Wang Yingchao, Shang Yuequan, Sun Hongyue, et al. Study of prediction of rockburst intensity based on efficacy coefficient method[J]. Rock and Soil Mechanics, 2010, 31(2): 529-534. (in Chinese))
[15] 宋英华, 江晨, 李墨潇, 等. 基于改进Smote-GBDT算法的岩爆预测模型[J]. 中国安全科学学报, 2023, 33(9): 25-32. (Song Yinhua, Jiang Chen, Li Moxiao, et al. Rockburst prediction model based on improved Smote-GBDT algorithm[J]. China Safety Science Journal, 2023, 33(9): 25-32. (in Chinese))
[16] Huang L Q, Li J, Hao H, et al. Micro-seismic event detection and location in underground mines by using Convolutional Neural Networks(CNN) and deep learning[J]. Tunnelling and Underground Space Technology, 2018, 81:265-276.
[17] 徐琛, 刘晓丽, 王恩志, 等. 基于组合权重-理想点法的应变型岩爆五因素预测分级[J]. 岩土工程学报, 2017, 39(12): 2245- 2252.(Xu Chen, Liu Xiaoli, Wang Enzhi, et al. Prediction and classification of strain mode rockburst based on five-factor criterion and combined weight-ideal point method[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(12): 2245- 2252. (in Chinese))
[18] 兰明, 刘志祥, 冯凡. 在线极限学习机在岩爆预测中的应用[J]. 安全与环境学报, 2014, 14(2): 90-93. (Lan Ming, Liu Zhixiang, Feng Fan. Attempt to study the applicability of the online sequential extreme learning machine to the rock burst forecast[J]. Journal of Safety and Environment, 2014, 14(2): 90-93. (in Chinese))
[19] 吴顺川, 张晨曦, 成子桥. 基于PCA-PNN原理的岩爆烈度分级预测方法[J]. 煤炭学报, 2019, 44(9): 2767-2776.(Wu Shunchuan, Zhang Chenxi, Cheng Ziqiao. Prediction of intensity classification of rockburst based on PCA-PNN principle[J]. Journal of China Coal Society, 2019, 44(9): 2767-2776. (in Chinese))
[20] 陈则黄, 李克钢, 李明亮, 等. 基于PCA-SOFM模型的岩爆烈度等级预测[J].地下空间与工程学报,2022,18(增2):934-942, 951. (Chen Zehuang, Li Kegang, Li Mingliang, et al. Prediction of rockburst intensity based on PCA-SOFM model[J]. Chinese Journal of Underground Space and Engineering, 2022,18(Supp.2):934-942, 951. (in Chinese))
[21] 周英豪, 王文杰, 卢西洲, 等. 岩爆灾害博弈论组合赋权预测模型及应用[J]. 中国安全科学学报, 2022, 32(7): 105-112. (Zhou Yinghao, Wang Wenjie, Lu Xizhou, et al. Combination weighting prediction model and application of rock burst disaster based on game theory[J]. China Safety Science Journal, 2022, 32(7): 105-112. (in Chinese))
[22] 张旭, 周绍武, 林鹏, 等. 基于熵权-集对的边坡稳定性研究[J].岩石力学与工程学报,2018, 37(增1):3400-3410. (Zhang Xu, Zhou Shaowu, Lin Peng et al. Research on slope stability based on entropy weighted set pairs [J]. Journal of Rock Mechanics and Engineering, 2018,37(Supp.1): 3400-3410. (in Chinese))
[23] 朱永生, 李振, 梁久正. 基于经验方法的铁矿深井围岩岩爆倾向性预测[J]. 地下空间与工程学报, 2020, 16 (2): 591-598. (Zhu Yongsheng, Li Zhen, Liang Jiuzheng. Prediction of rockburst proneness of surrounding rock in iron mine based on empirical method[J]. Chinese Journal of Underground Space and Engineering, 2020, 16 (2): 591-598. (in Chinese))
[24] 周科平, 林允, 胡建华, 等. 基于熵权-正态云模型的岩爆烈度分级预测研究[J]. 岩土力学, 2016, 37(S增1): 596-602. (Zhou Keping, Lin Yun, Hu Jianhua, et al. Grading prediction of rockburst intensity based on entropy and normal cloud model [J]. Rock and Soil Mechanics, 2016, 37(Supp.1): 596-602. (in Chinese))
[25] 李明亮, 李克钢, 秦庆词等.基于改进组合赋权-TOPSIS 法的岩爆倾向性评判模型[J]. 中国安全生产科学技术, 2020, 16(3): 74- 80.(Li Mingliang, Li Kegang, Qin Qingci, et al. Judgment model of rock burst tendency based on improved combination weighting-TOPSIS method[J]. Journal of Safety Science and Technology, 2020, 16(3): 74- 80. (in Chinese))
[26] 刘秋艳, 吴新年. 多要素评价中指标权重的确定方法评述[J]. 知识管理论坛, 2017, 2 (6): 500-510.(Liu Qiuyan, Wu Xinnian. Review on weighting methods of indexes in the multi-factor evaluation. [J]. Knowledge Management Forum, 2017, 2 (6): 500-510. (in Chinese))
[27] 张晨, 王清, 陈剑平, 等. 金沙江流域泥石流的组合赋权法危险度评价[J].岩土力学, 2011, 32(3): 831-836. (Zhang Chen, Wang Qing, Chen Jianping, et al. Evaluation of debris flow risk in Jinsha River based on combined weight process[J]. Rock and Soil Mechanics, 2011, 32(3): 831-836. (in Chinese))
[28] 殷欣, 刘泉声, 王心语, 等. 基于组合赋权和属性区间识别理论的岩爆烈度分级预测模型[J]. 煤炭学报, 2020, 45(11): 3772-3780. (Yin Xin, Liu Quansheng, Wang Xinyu, et al. Prediction model of rockburst intensity classification based on combined weighting and attribute interval recognition theory[J]. Journal of China Coal Society, 2020, 45(11): 3772-3780. (in Chinese))
[29] 周科平, 雷涛, 胡建华. 深部金属矿山RS-TOPSIS岩爆预测模型及其应用[J]. 岩石力学与工程学报, 2013, 32(增2): 3706-3710. (Zhou Keping, Lei Tao, Hu Jianhua. RS-TOPSIS Model of rockburst prediction in deep metal mines and its application[J]. Chinese Journal of Rock Mechanics and Engineering, 2013, 32(Supp.2): 3706-3710. (in Chinese))
[30] 张传庆, 卢景景, 陈珺, 等. 岩爆倾向性指标及其相互关系探讨[J]. 岩土力学, 2017, 38(5):1397-1404.(Zhang Chuanqing, Lu Jingjing, Chen Jun, et al. Discussion on rock burst proneness indexes and their relation[J]. Rock and Soil Mechanics, 2017, 38(5):1397-1404. (in Chinese))
[31] 中华人民共和国住房和城乡建设部. 工程岩体分级标准(GB/T 50218-2014)[S]. 北京:中国建筑工业出版社, 2014. (Ministry of Housing and Urban-Rural Development of the People's Republic of China. Classification standards for engineering rock masses (GB/T 50218-2014)[S]. Beijing: China Construction Industry Press, 2014. (in Chinese))
[32] Peng X, Li D Y, Zhao G Y, et al. Characteristics and mechanism of rockburst at five deep gold mines in Jiaodong Peninsula of China[J]. International Journal of Rock Mechanics and Mining Sciences, 2023, 17(1):1365-1609.
