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Getting scale-free network from a small world network without growth

机译:从一个没有增长的没有增长的小世界网络获取无扩展网络

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A method that can be used to get scale-free network from a small-world network without growth under the mechanism of preferential attachment is proposed. Unlike the normal BA growth network model, in our model we remove an old node with a probability scaling with the degree of the node before adding a new node into the network, that make the size of the network fixed, but the nodes and edges are not fixed. If an old node has less degree, it has a larger probability to be removed, and its edges are deleted at the same time. It is found that the degree distribution based on our model obeys a form like power-law of BA model, but the scope of degree distribution in our model is much smaller than BA model. Therefore, the degree distribution's heave tail in our model is thinner than that in the normal BA model; thus it is different from the normal BA model. Meanwhile, there are some other properties in our model, for instance, the average clustering coefficient decreases with the renewed ratio and the power-law exponent increases with the renewed ratio to a limited value, which is equal to that in the normal BA model.
机译:提出了一种方法,可以用于从优惠附件机制下没有增长的小世界网络从小世界网络中获得无量比网络。与正常的BA增长网络模型不同,在我们的模型中,我们在将新节点添加到网络之前,我们删除了具有概率缩放的旧节点,该节点在网络中添加了网络的大小,但节点和边缘不固定。如果旧节点具有较少程度,则它具有更大的概率才能删除,并且其边缘同时删除。结果发现,基于我们的模型的程度分布,obeys一种形式,如BA模型的权力法,但我们模型中程度分布的范围远小于BA模型。因此,我们模型中的学位分布的升降尾部比正常的BA模型更薄;因此,它与正常的BA模型不同。同时,在我们的模型中存在一些其他特性,例如,随着更新的比率降低的平均聚类系数减小,电源指数随着续期的比率而增加,与普通BA模型中的有限值相等。

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