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A growth model for directed complex networks with power-law shape in the out-degree distribution

机译:有度分布下有幂律形状的有向复杂网络的增长模型

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摘要

Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1.
机译:已经发布了许多增长模型来对实际复杂网络的行为进行建模。这些模型能够复制此类网络的一些拓扑属性。但是,在大多数这些增长模型中,添加到网络的节点的出站链接数(即出度)是恒定的,也就是说,网络中的所有节点都具有相同数量的出站链接。在其他模型中,最终的度外分布随泊松或指数分布而衰减。然而,已经发现,在实际的复杂网络中,向外度分布作为幂律衰减。为了获得具有幂律行为的外向度分布,已经提出了一些模型。这项工作引入了一个新模型,该模型可以获取出度分布,该分布可以作为幂律衰减,且指数范围为0到1。

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