[1] O'NEILL C, ROBINSON A M, INGLETON S. Mitigating the effects of firebomb and blast attacks on metro systems [J]. Procedia-Social and Behavioral Sciences, 2012, 48:3 518-3 527. [2] National Consortium for the Study of Terrorism and Responses to Terrorism (START). Global terrorism database [EB/OL]. [2021-01-04]. https://www.start.umd.edu/gtd. [3] 邱凌峰,韩昕格,胡啸峰.基于机器学习的恐怖袭击事件后果预测方法研究[J]. 中国安全生产科学技术,2020, 16(1): 175-181. QIU Lingfeng, HAN Xin'ge, HU Xiaofeng. Study on method of consequence prediction for terrorist attacks based on machine learning [J]. Journal of Safety Science and Technology, 2020, 16(1): 175-181. [4] NIZAMANI S, MEMON N. Detecting terrorism incidence type from news summary[C]. Proceedings of 2011 SSITE International Conference on Computers and Advanced Technology in Education,2011:95-102. [5] SIVAMAN R, SRINIVASAN S, CHANDRASEKERAN R. Big data on terrorist attacks: an analysis using the ensemble classifier approach [EB/OL]. [2021-01-04].https://edlib.net/2015/icidret/icidret2015042.pdf. [6] 肖圣龙,陈昕,李卓.面向社会安全事件的分布式神经网络攻击方式分类方法[J].计算机应用,2017,37(10):2 794-2 798. XIAO Shenglong, CHEN Xin, LI Zhuo. Distributed neural network for classification of attack behavior to social security events [J]. Journal of Computer Applications, 2017, 37(10):2 794-2 798. [7] 段照斌,杜海龙,张鹏.基于QAR2Vec模型的QAR数据特征提取[J].中国安全科学学报,2021,31(1):145-152. DUAN Zhaobin,DU Hailong,ZHANG Peng. Feature extraction of QAR data based on QAR2Vec model [J]. China Safety Science Journal, 2021, 31(1):145-152. [8] VINCENT P, LAROCHELLE H, BENGIO Y, et al. Extracting and composing robust features with denoising autoencoders[C].Proceedings of the 25th International Conference on Machine Learning,2008:1 096-1 103. [9] 徐丹,代勇,纪军红.基于卷积神经网络的驾驶人行为识别方法研究[J].中国安全科学学报,2019, 29(10): 12-17. XU Dan,DAI Yong,JI Junhong. Research on driver behavior recognition method based on convolutional neural network [J]. China Safety Science Journal, 2019, 29(10): 12-17. [10] 林海飞,高帆,严敏,等.煤层瓦斯含量PSO-BP神经网络预测模型及其应用[J].中国安全科学学报,2020,30(9):80-87. LIN Haifei,GAO Fan,YAN Min,et al.Study on PSO-BP neural network prediction method of coal seam gas content and its application[J].China Safety Science Journal,2020,30(9):80-87. [11] BENGIO Y. Learning deep architectures for AI [J]. Foundations and Trends in Machine Learning, 2009, 2(1):1-127. |