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提出了一种复杂网络模型的新机制,在网络生长的过程中新节点的加入是使其预期的效用最大.其中,效用不仅考虑其连接的利益,同时也考虑建立连接的地理信息.我们深入分析了地理位置信息引入对网络度分布、簇系数和匹配方式的影响.仿真结果表明,该建模机制能够得到各种不同拓扑结构的复杂网络,包括随机网络、小世界网络、无标度网络等.并且地理信息对网络的匹配方式有重要的影响.
Proposed a new mechanism of complex network model, the new node in the process of network growth is to maximize its expected utility.Which utility not only consider the interests of their connection, but also consider the establishment of the connection of geographic information. The influence of geographical location information introduction on network degree distribution, clustering coefficient and matching mode is analyzed.The simulation results show that this modeling mechanism can obtain a variety of complex networks with different topologies, including stochastic networks, small-world networks, scale-free networks Etc. And geographical information has a significant impact on the way the network is matched.