标题： 动态增长规则下的演化网络模型 显示英文标题

标题： Evolving network models under a dynamic growth rule

摘要： 在包含节点添加和删除的动态增长规则下，研究了演变的网络模型。 通过在每个时间步以概率$P_a$添加一个节点或以概率$P_d=1-P_a$删除一个节点，其中$P_a$和$P_d$由逻辑斯蒂种群方程确定，研究了网络的拓扑特性。 获得了现实系统中观察到的所有胖尾度分布，提供了证据表明添加和删除机制可以导致现实系统度分布的多样性。 此外，发现网络表现出非平稳的度分布，从幂律分布变为指数分布，或从指数分布变为高斯分布。 这些结果有望为现实复杂网络的形成和演化提供一些启示。 显示英文摘要

摘要： Evolving network models under a dynamic growth rule which comprises the addition and deletion of nodes are investigated. By adding a node with a probability $P_a$ or deleting a node with the probability $P_d=1-P_a$ at each time step, where $P_a$ and $P_d$ are determined by the Logistic population equation, topological properties of networks are studied. All the fat-tailed degree distributions observed in real systems are obtained, giving the evidence that the mechanism of addition and deletion can lead to the diversity of degree distribution of real systems. Moreover, it is found that the networks exhibit nonstationary degree distributions, changing from the power-law to the exponential one or from the exponential to the Gaussian one. These results can be expected to shed some light on the formation and evolution of real complex real-world networks.