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中国物理学会期刊

节点数加速增长的复杂网络生长模型

CSTR: 32037.14.aps.55.4051

Growing complex network model with acceleratingly increasing number of nodes

CSTR: 32037.14.aps.55.4051
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  • 受某些实际网络节点数按几何级数增长现象的启发,构造了每个时间步中按当前网络规模成比例地同时加入多个节点的节点数加速增长的网络模型.研究表明,在增长率不是很大的情况下网络度分布仍然是幂律的,但在不同的增长率r下幂律指数是不同的.得到了幂律指数介于2到3之间可调的无标度网络模型,并解析地给出了幂律指数随增长率变化的函数关系.数值模拟还显示,网络的平均最短距离随r减小而簇系数随r增大.

     

    Inspired by the observation that some real-life networks' sizes grow as a geometric series, a growing complex network model with acceleratingly increasing number of nodes is proposed. At each time step, the number of newly added nodes is proportional to the size of the network. This network shows scale-free property when the growing rate r is not large, and its power-law exponent is tunable from 2 to 3 through r. The average path length decreases and clustering coefficient increases with r respectively. In addition, we also give an analytical solution about power-law exponent versus r that agrees well with the simulation result.

     

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