节点删除对网络结构的影响
Effect of node deleting on network structure
摘要：
对现实世界中各种网络结构的不断了解揭示了它们复杂的多机制演化过程。因此，更好地了解这些网络化复杂系统的结构和演变需要我们以更详细和现实的方式描述此类过程。本文引入了一种新的网络增长规则，它包括节点的添加和删除，并提出了一个演化网络模型来研究节点删除对网络结构的影响。研究发现，随着节点删除的引入，网络结构发生了显著的变化。特别地，随着节点删除强度的增加，网络的度分布经历了从无标度到指数形式的转变。同时，非平凡的离散度关联作为网络演化的自然结果在模型中自发发展。我们还证明了，节点删除引入模型中不会破坏一个不断增长的网络的连通性，只要边的增长率不是太小。此外，研究发现节点删除会削弱但不能消除网络的小世界效应，一般会降低网络的聚类系数。
英文摘要：
The ever-increasing knowledge of the structure of various real-world networks has uncovered their complex multi-mechanism-governed evolution processes. Therefore, a better understanding of the structure and evolution of these networked complex systems requires us to describe such processes in a more detailed and realistic manner. In this paper, we introduce a new type of network growth rule which comprises addition and deletion of nodes, and propose an evolving network model to investigate the effect of node deleting on network structure. It is found that, with the introduction of node deleting, network structure is significantly transformed. In particular, degree distribution of the network undergoes a transition from scale-free to exponential forms as the intensity of node deleting increases. At the same time, nontrivial disassortative degree correlation develops spontaneously as a natural result of network evolution in the model. We also demonstrate that node deleting introduced in the model does not destroy the connectedness of a growing network so long as the increasing rate of edges is not excessively small. In addition, it is found that node deleting will weaken but not eliminate the small-world effect of a growing network, and generally it will decrease the clustering coefficient in a network.
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。
