基于社会网络与事件关联的恐怖事件监测与识别

发布时间：2018-05-27 12:37

  本文选题：恐怖组织网络 + 变化检测　； 参考：《科技导报》2017年09期

【摘要】：恐怖组织的社会网络结构变化与恐怖事件的发生具有一定的关联性。基于此关联,通过监测恐怖组织社会网络的变化,可以实时、有效地识别恐怖事件。将基于社会网络变化检测的恐怖事件监测与识别问题视为分类问题,并通过神经网络模型进行分类研究。以某一时刻是否发生恐怖事件为标准,对恐怖组织社会网络进行分类;通过网络分析技术,得出网络的参数指标,建立混合算法改进的神经网络模型;将网络的参数指标与恐怖事件发生情况分别作为输入和输出,对神经网络进行训练与测试。案例分析和对比结果表明,基于神经网络模型的社会网络变化检测方法具备较好的恐怖事件监测与识别能力;该方法可在一定程度上弥补现有方法正确率不高、通用性不强、检测结果与恐怖事件实际发生的相关性不高等不足。
[Abstract]:The change of social network structure of terrorist organizations is related to the occurrence of terrorist events. Based on this correlation, terrorist events can be recognized in real time and effectively by monitoring the changes of social networks of terrorist organizations. The problem of terrorist event detection and identification based on social network change detection is considered as a classification problem, and the classification is studied by neural network model. The social network of terrorist organization is classified according to whether or not a terrorist event occurs at a certain time, the parameter index of network is obtained by network analysis technology, and the improved neural network model of hybrid algorithm is established. The parameters of the neural network and the occurrence of terrorist events are taken as input and output respectively to train and test the neural network. The results of case analysis and comparison show that the social network change detection method based on neural network model has a better ability to detect and identify terrorist events, and this method can make up for the lack of accuracy and universality of the existing methods to some extent. The correlation between the detection results and the actual occurrence of terrorist events is not high enough.
【作者单位】： 国防科技大学信息系统与管理学院;
【基金】：国家自然科学基金项目(71473263) 高等学校博士学科专项科研基金项目(20134307110020)
【分类号】：C912.3
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本文编号：1942113