基于网络超链接信息熵的节点重要性序结构演化建模分析

胡钢; 牛琼; 许丽鹏; 卢志宇; 过秀成

doi:10.12263/DZXB.20211307

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基于网络超链接信息熵的节点重要性序结构演化建模分析

学术论文 | 更新时间：2025-12-08

- 基于网络超链接信息熵的节点重要性序结构演化建模分析
- The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy
- 电子学报 2022年50卷第11期页码：2638-2644
- 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.东南大学交通学院, 江苏南京 210096
- 作者简介：
  
  [ "胡钢男, 1970年出生于甘肃省天水市;安徽工业大学管理科学与工程学院副教授, 硕士生导师; 研究方向: 多属性决策、复杂网络系统建模仿真与均衡分析.E-mail: hug_2004@126.com" ]
  [ "牛琼男, 1997年出生于安徽省亳州市;安徽工业大学在读硕士研究生, 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: NiuQiongNQ@163.com" ]
- 基金信息：
  
  国家自然科学基金(71772002);安徽省自然科学基金(2108085MG236);安徽省高校自然科学研究项目(KJ2021A0385);安徽省高校研究生科学研究项目(YJS20210356)
- DOI：10.12263/DZXB.20211307
  中图分类号： TP393
- 收稿：2021-09-23，
  
  修回：2022-01-08，
  
  纸质出版：2022-11-25
- 稿件说明：
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胡钢,牛琼,许丽鹏等.基于网络超链接信息熵的节点重要性序结构演化建模分析[J].电子学报,2022,50(11):2638-2644.

HU Gang,NIU Qiong,XU Li-peng,et al.The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy[J].ACTA ELECTRONICA SINICA,2022,50(11):2638-2644.
胡钢,牛琼,许丽鹏等.基于网络超链接信息熵的节点重要性序结构演化建模分析[J].电子学报,2022,50(11):2638-2644. DOI： 10.12263/DZXB.20211307.

HU Gang,NIU Qiong,XU Li-peng,et al.The Model to Analyses of Node Importance Order Structure Evolution Based on Network Hyperlink Information Entropy[J].ACTA ELECTRONICA SINICA,2022,50(11):2638-2644. DOI： 10.12263/DZXB.20211307.

摘要

动态复杂网络在时空演化过程中，网络节点重要性层内交互关系和层间耦合关系可以更为准确对时序网络节点序结构演化进行分析.本文提出基于网络超链接信息熵的节点重要性序结构演化模型.分析时序网络层内节点超链接信息熵重要性排序结果，得到时序网络节点相邻时间层与跨时间层节点重要性排序模型.节点超链接信息熵总结相邻时间层与跨时间层节点相似性耦合效应.通过SIR（Susceptible Infected Recovered）模型检验节点传播效率进行实证网络仿真，结果与经典时序网络模型相比，本文模型

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15.49400043

2.70933342

值在各时间层均有提高，最高为11.310%.

Abstract

In the time evolution of dynamic complex networks

the intra-layer interaction relationship and inter-layer coupling relationship of the importance of network nodes can be more accurately analyzed for the evolution of the node order structure of the time ordered networks. In this paper

a model of node importance order structure evolution based on network hyperlink information entropy is proposed. Through the results of the importance ranking of node hyperlink information entropy within the temporal network layer

the importance ranking model of nodes in the adjacent temporal layer and across temporal layers of the temporal network is analyzed. The entropy of node hyperlink information summarizes the coupling effect of similarity between adjacent temporal layers and inter-temporal layers. An empirical network simulation was conducted to check the node propagation efficiency by SIR(Susceptible Infected Recovered) model. Compared with the classical temporal network model

the

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15.49400043

2.70933342

value of this model was improved in all time layers

with the highest value of 11.310%.

关键词

Keywords

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