复杂网络中的轨迹分析
Analyzing Trails in Complex Networks
摘要：
比复杂网络的错综复杂的组织更有趣的是这种结构所基于的系统的动力学行为。在众多类型的动力学中，一个特别有趣的类别涉及移动代理在复杂网络中通过随机行走和扩张过程前进时留下的痕迹的演变。步道的产生存在于行人交通、信息流、新陈代谢等多种动力学过程中。与足迹相关的重要问题包括当足迹的完整知识缺失时，足迹的重建和其来源的识别。此外，在多智能体系统中的步道以下代表了一个特别有趣的情况，行人动态和群集智能。目前的工作解决这三个问题，同时考虑到永久和短暂的标记留在访问过的节点。不同的拓扑结构被认为是轨迹重建和轨迹源识别，包括四个复杂网络模型和四个实际网络，即互联网，美国航空公司网络，电子邮件网络和复杂网络研究人员的科学合作网络。我们的研究结果表明，网络的拓扑结构在轨迹重建，源识别和代理动力学的影响。
英文摘要：
Even more interesting than the intricate organization of complex networks are the dynamical behavior of systems which such structures underly. Among the many types of dynamics, one particularly interesting category involves the evolution of trails left by moving agents progressing through random walks and dilating processes in a complex network. The emergence of trails is present in many dynamical process, such as pedestrian traffic, information flow and metabolic pathways. Important problems related with trails include the reconstruction of the trail and the identification of its source, when complete knowledge of the trail is missing. In addition, the following of trails in multi-agent systems represent a particularly interesting situation related to pedestrian dynamics and swarming intelligence. The present work addresses these three issues while taking into account permanent and transient marks left in the visited nodes. Different topologies are considered for trail reconstruction and trail source identification, including four complex networks models and four real networks, namely the Internet, the US airlines network, an email network and the scientific collaboration network of complex network researchers. Our results show that the topology of the network influence in trail reconstruction, source identification and agent dynamics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
