基于多局域的恐怖组织网络择优增长演化模型

恐怖组织网络是一种特殊的复杂网络，其时空演化规律反映出恐怖组织活动的特征.为更准确地理解恐怖组织网络的动态演化规律，提出一种基于多局域的恐怖组织网络择优增长演化模型，并对此模型进行了仿真与模拟.该模型能准确地描述在局部信息条件下，新节点的择优和网络的增长过程及其规律；并且利用网络信息中心度来衡量恐怖组织网络节点的信念水平，动态地刻画了恐怖组织网络的增长过程.实验结果表明:恐怖组织网络的局域度分布仍服从幂律分布，网络信息中心度具有集中与分散性的特征；最后，对多个恐怖组织网络按该模型进行仿真演化，验证了该模型的准确性与科学性.

A Preferential Growing Evolution-model of Terrorist Networks Based on Multi-local Network

The network of terrorist organizations is a special complex network, and its spatiotemporal evolution process reflects the characteristics of terrorist organization activities. To more accurately depict the dynamic evolution process of terrorist network, this paper puts forward a preferential-growing evolution model of terrorist networks based on the multi-local network, and the model is simulated. The model can accurately describe the growth of new nodes and the growth process of network under the condition of local information. We use the node network information center degree to measure the level of terrorist beliefs, dynamic characterization of a terrorist network growth process. The experimental results show:in the terrorist networks, the degree distribution of local network follows the power-law distribution, the network information center degree of the nodes of local network has the characteristics of centralized and decentralized. Finally, the model is verified with the data of terrorist networks. The verification results show that the model is accurate.