加速增长对加权复杂网络演化的影响
Effects of accelerating growth on the evolution of weighted complex networks
摘要：
许多真实系统具有加速统计，其中边的总数增长得比网络大小更快。本文提出了一个简单的具有加速增长的加权网络模型。我们推导出解析表达式的演变和分布的强度，程度和重量，这是相关的加速增长。我们还发现，加速增长决定了网络的聚类系数。有趣的是，强度，度和重量的分布显示从无标度的指数形式的过渡时，加速增长的参数从一个小到大的值增加。所有的理论预测成功地与广泛的数值模拟进行了对比。
英文摘要：
Many real systems possess accelerating statistics where the total number of edges grows faster than the network size. In this paper, we propose a simple weighted network model with accelerating growth. We derive analytical expressions for the evolutions and distributions for strength, degree, and weight, which are relevant to accelerating growth. We also find that accelerating growth determines the clustering coefficient of the networks. Interestingly, the distributions for strength, degree, and weight display a transition from scale-free to exponential form when the parameter with respect to accelerating growth increases from a small to large value. All the theoretical predictions are successfully contrasted with extensive numerical simulations.
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