电子学报 ›› 2020, Vol. 48 ›› Issue (12): 2402-2408.DOI: 10.3969/j.issn.0372-2112.2020.12.016

• 学术论文 • 上一篇    下一篇

基于重要度传输矩阵的复杂网络节点重要性辨识方法

胡钢1, 高浩1, 徐翔2, 许丽鹏1   

  1. 1. 安徽工业大学管理科学与工程学院, 安徽马鞍山 243032;
    2. 国防科技大学信息系统工程重点实验室, 湖南长沙 410073
  • 收稿日期:2019-07-04 修回日期:2020-07-22 出版日期:2020-12-25
    • 作者简介:
    • 胡钢 男,1970年出生,甘肃天水人,博士后,副教授主要研究方向为复杂网络系统建模仿真与均衡分析、多属性决策.E-mail:hug_2004@126.com;高浩 男,1995年出生,安徽宿州人,现为在读硕士研究生,主要研究方向为复杂网络系统建模仿真与均衡分析、多属性决策.E-mail:872165680@qq.com

Importance Identification Method of Complex Network Nodes Based on Importance Transfer Matrix

HU Gang1, GAO Hao1, XU Xiang2, XU Li-peng1   

  1. 1. School of Management Science and Engineering, Anhui University of Technology, Maanshan, Anhui 243032, China;
    2. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, Hunan 410073, China
  • Received:2019-07-04 Revised:2020-07-22 Online:2020-12-25 Published:2020-12-25

摘要: 复杂网络中节点重要性辨识对分析网络结构和功能具有重要作用.为了辨识节点重要性,分析节点自身和关联节点的作用,本文构建了一种基于重要度传输矩阵的节点重要性辨识模型.首先,基于关联节点与节点之间的最优路径长度、最优路径数目和信息传播率定义了节点间的传输能力.其次,依据度值和传输能力构建重要度传输矩阵,综合节点局部重要性和全局属性指标评价节点的重要性.最后,对"ARPA"网络和四个真实网络进行破坏性仿真分析,结果本文方法表明对网络造成更大的破坏,证明了该方法的有效性和可靠性.

关键词: 复杂网络, 节点重要性, 信息传播率, 传输能力, 重要度传输矩阵

Abstract: In complex networks, node importance identification plays an important role in analyzing the structure and function. In order to identify the node's importance and analyze the role of nodes themselves and associated nodes, we construct a node importance identification model based on importance transfer matrix. Firstly, the transmission capability between nodes is defined based on the optimal path length, the number of optimal paths and the information propagation rate between the associated nodes and the nodes. Secondly, the node degree and transmission capacity are used to construct the importance transmission matrix, and the local importance and global attribute index of the node are integrated to evaluate the importance of the node. Finally, destructive simulation analysis on the "ARPA" network and four real networks show that this method causes more damage to the network, which proves the method's effectiveness and reliability.

Key words: complex network, node's importance, information transmission rate, transmission capacity, importance transfer matrix

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