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Age-based model for weighted network with general assortative mixing

机译:综合分类混合的加权网络年龄模型

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In this paper, we propose an evolutionary model for weighted networks by introducing an age-based mutual selection mechanism. Our model generates power-law distributions of degree, weight, and strength, which are confirmed by analytical predictions and are consistent with real observations. The investigation of the relationship between clustering and the connectivity of nodes suggests hierarchical organization in the weighted networks. Furthermore, both assortative and disassortative properties can be naturally obtained by tuning a parameter alpha, which controls the strength of age-based preferential attachments. Since the age information of nodes is easier to acquire than the degree and strength of nodes, and almost all empirically observed structural and weighted properties can be reproduced by the simple evolutionary regulation, our model may reveal some underlying mechanisms that are key for the evolution of weighted complex networks. Published by Elsevier B.V.
机译:在本文中,我们通过引入基于年龄的互选机制,提出了加权网络的演化模型。我们的模型会生成程度,重量和强度的幂律分布,这些幂律分布已通过分析预测得到确认,并且与实际观测值一致。对群集和节点连接性之间关系的研究表明,加权网络中具有层次结构。此外,可以通过调整参数alpha来自然地获得分类和非分类属性,该参数控制基于年龄的优先附件的强度。由于节点的年龄信息比节点的程度和强度更容易获取,并且几乎所有凭经验观察到的结构和加权特性都可以通过简单的进化规律来再现,因此我们的模型可能揭示了一些潜在的机制,这些机制是进化的关键。加权复杂网络。由Elsevier B.V.发布

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