基于多层结构的恐怖组织网络协同演化与干预策略研究

恐怖组织网络协同演化是恐怖组织活动的一个重要机制与特征，对其研究方法的欠缺成为了当前在反恐预警防范和策略构建应用中的瓶颈问题。本项目在前期研究基础上，通过引入多层网络模型研究恐怖组织网络的协同演化过程和机制，进而探索面向事件的活动监测和干预策略计算实验的方法技术。首先，以国内典型恐怖组织活动为背景，基于要素分解规范和时序网络模型构建恐怖组织多层动态网络模型；其次，借鉴机器学习的思想研究恐怖组织多层网络协同演化的个体行为模式识别方法，从而构建多层网络协同演化模型，揭示恐怖组织协同演化机制与规律；第三，基于监督学习方法提出面向事件的协同演化特征监测方法，为恐怖活动预警提供方法和手段；最后，构建恐怖组织恢复力模型，建立基于Agent的恐怖组织弹性网络计算实验框架，开展多种形式的干预策略计算实验。通过研究，提出有效的网络动态监测和干预策略构建方法，为恐怖活动监测、预警和干预提供理论依据和技术支持。

The evolution of terrorist organization network is a significant mechanism and feature in terrorist organizational activities, and the lack of research methods on it has become a bottleneck in current anti-terrorism application of early warning and strategy construction. Based on the previous research, this project aims to study the co-evolution process and mechanism of the terrorist organization network by introducing the multilayer networks model, and then explore the method of event-oriented activity monitoring and the technology of intervention strategy computational experiment. First, based on the background of domestic typical terrorist organization, we construct the multilayer dynamic network model of the terrorist organization based on the element decomposition specification and the time series network model. Second, we propose the individual behavior identification method of multilayer terrorist organization network in the process of co-evolution based on the idea of machine learning. Then the mechanism and law of terrorist organization co-evolution can be analyzed. Third, we propose the event-oriented co-evolution feature monitoring method based on the supervised learning method, which can provide the method and means for the early warning of terrorist activities. Finally, by modeling the resilience of terrorist organization, the agent based computational experiment framework of resilient terrorist organization network is proposed to carry out various forms of intervention strategy computational experiments. This project aims to propose effective methods on network dynamic monitoring and intervention construction, so as to provide theoretical basis and technical support for anti-terrorism applications of terrorist activity monitoring, early warning and intervention.