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

HU Gang; GAO Hao; XU Xiang; XU Li-peng

doi:10.3969/j.issn.0372-2112.2020.12.016

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

更新时间：2025-12-08

- Importance Identification Method of Complex Network Nodes Based on Importance Transfer Matrix
- Acta Electronica Sinica Vol. 48, Issue 12, Pages: 2402-2408(2020)
- 作者机构：
  
  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
  3. 安徽工业大学管理科学与工程学院,安徽,马鞍山,243032
  4. 国防科技大学信息系统工程重点实验室,湖南,长沙,410073
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2020.12.016
  CLC： TP393
- Published Online：25 December 2020，
  
  Published：2020
- 稿件说明：
移动端阅览
HU Gang, GAO Hao, XU Xiang, et al. Importance Identification Method of Complex Network Nodes Based on Importance Transfer Matrix[J]. Acta Electronica Sinica, 2020, 48(12): 2402-2408.
DOI：

HU Gang, GAO Hao, XU Xiang, et al. Importance Identification Method of Complex Network Nodes Based on Importance Transfer Matrix[J]. Acta Electronica Sinica, 2020, 48(12): 2402-2408. DOI： 10.3969/j.issn.0372-2112.2020.12.016.

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.

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.

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