复杂网络中的社团结构特性分析-控制理论与控制工程专业论文.docxVIP

摘要 摘要 PAGE PAGE 2 的新算法，衡量社团划分算法好坏的基准图。最后展望了该领域的未 来研究方向。 2 在保持网络一阶、二阶和三阶度相关特性不变的情形下，利用随机 重连方法和社团检测算法研究了复杂网络的社团结构特性。仿真分析 发现保持网络三阶度相关特性不变的随机重连方法所构造的网络则 可以很高精度地呈现原有网络的社团特性，从而表明网络的社团结构 可以由三阶度相关特性有效地刻画（不需要更高阶）。本文的研究提 供了一种网络构造方法，即利用三阶随机重连方法可构造出能够体现 真实网络社团结构这一特性的随机网络。 3 提出了一种可用于寻找加权网络中社团结构特性的算法，使得新算 法能够同时体现出网络中社团的层次性和重叠性，并能够在较短时间 内处理大规模的网络数据。其次提出了一种基于微调策略分析动态网 络演化中社团特性的算法，能够在网络规模变化不大的前提下对网络 高效地进行社团特性的分析。从而为动态网络的社团研究提供了一种 较好的途径。最后利用基准图对三种经典算法的优劣性进行了比较。 4 利用新算法对在线社会网络 Wealink（ HYPERLINK / ）的 结构特性和动态演化进行了实证分析，其中包含了网络规模、社团结 构、重叠性节点、聚类系数和度分布等特性，重点研究了若邻网中社 团结构的动态演化。 关键词：复杂网络，社团结构，模块度，随机重连，度相关特性， 层次性，重叠性，若邻网，实证分析 Abs Abstract PAGE PAGE 1 ANALYSIS OF COMMUNITY STRUCTURE IN COMPLTEX NETWORKS ABSTRACT The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of complex networks is community structure. A community structure is a densely connected subset of nodes that is only sparsely linked to the remaining networks. Detecting communities in complex networks is of great importance in sociology, biology and computer science and so on. In recent years, a lot of community discovery algorithms have been proposed aiming at different kinds of large scale complex networks. In this paper, we have summarized some latest representative algorithms and have pointed out the important progress in this research area. By which order of degree distribution of networks, the community structure in complex networks can be remarkably maintained is always one problem up in the air in the network science. Then, we have studied the problem with the aid of random rewiring algorithm and community structure detection algorithm. Finally, we have constructed a new algorithm which can detect the hierarchical and overlapping communities in weighted networks. We have analyzed the characteristics of Wealink, especially the dynamic evolutions of communities in the network. The main contributions of the dissertation are summarized