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TOWARD A HARMONIOUS UNIFYING HYBRID MODEL FOR ANY EVOLVING COMPLEX NETWORKS

机译:建立任何不断发展的复杂网络的和谐统一混合模型

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The current interest in complex networks is a part of a broader movement towards research on complex systems. Motivation of this work raises the two challenging questions: (i) Are real networks fundamentally random preferential attached without any deterministic attachment for both un-weighted and weighted networks? (ii) Is there a coherent physical idea and model for unifying the study of the formation mechanism of complex networks? To answer these questions, we propose a harmonious unifying hybrid preferential model (HUHPM) to a certain class of complex networks, which is controlled by a hybrid ratio, d/r, and study their behavior both numerically and analytically. As typical examples, we apply the concepts and method of the HUHPM to un-weighted scale-free networks proposed by Barabasi and Albert (BA), weighted evolving networks proposed by Barras, Bartholomew and Vespignani (BBV), and the traffic driven evolution (TDE) networks proposed by Wang et al., to get the so-called HUHPM-BA, HUHPM-BBV and HUHPM-TDE networks. All the findings of topological properties in the above three typical HUHPM networks give certain universal meaningful results which reveal some essential hybrid mechanisms for the formation of nontrivial scale-free and small-world networks.
机译:当前对复杂网络的兴趣是对复杂系统进行更广泛研究的一部分。这项工作的动机提出了两个具有挑战性的问题:(i)真实网络是否从根本上随机附有优先权,而对未加权和加权网络都没有确定性的依附? (ii)是否有统一的物理思想和模型来统一对复杂网络形成机制的研究?为了回答这些问题,我们提出了针对一类复杂网络的和谐统一混合优先模型(HUHPM),该模型由混合比率d / r控制,并在数值和分析上研究它们的行为。作为典型示例,我们将HUHPM的概念和方法应用于Barabasi和Albert(BA)提出的未加权无标度网络,Barras,Bartholomew和Vespignani(BBV)提出的加权演进网络以及流量驱动的演进( Wang等人提出的TDE网络,以获得所谓的HUHPM-BA,HUHPM-BBV和HUHPM-TDE网络。以上三个典型的HUHPM网络中所有拓扑特性的发现都给出了某些普遍有意义的结果,这些结果揭示了形成非平凡的无标度和小世界网络的一些必要的混合机制。

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