时间序列复杂网络分析中的可视图方法研究综述

李海林; 王杰; 周文浩; 蔡煜; 林伟滨

doi:10.12263/DZXB.20230082

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时间序列复杂网络分析中的可视图方法研究综述

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- 时间序列复杂网络分析中的可视图方法研究综述
- A Review of Visibility Graph Methods Research in Time Series Complex Network Analysis
- 电子学报 2023年51卷第9期页码：2598-2622
- 作者机构：
  
  1.华侨大学工商管理学院，福建泉州 362021
  2.泉州师范学院商学院，福建泉州 362021
- 作者简介：
  
  [ "李海林男，1982年生.博士.华侨大学工商管理学院教授、博士生导师.主要研究方向为计算机应用、数据挖掘、大数据分析.E-mail: hailin@hqu.edu.cn" ]
  [ "王杰男，2000年生.华侨大学工商管理学院本科生.主要研究方向为计算机应用、数据挖掘.E-mail: 1752624298@qq.com" ]
  [ "周文浩男，1997年生.华侨大学工商管理学院博士研究生.主要研究方向为数据分析、计算机应用.E-mail: wenhaoz2021@stu.hqu.edu.cn" ]
  [ "蔡煜男，2001年生.华侨大学工商管理学院本科生.主要研究方向为计算机应用.E-mail: 1512875381@qq.com" ]
  [ "林伟滨(通讯作者) 男，1990年出生.华侨大学工商管理学院博士研究生.主要研究方向为数据分析、计算机应用.E-mail: lwb@qztc.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(71771094);国家社会科学基金(22FGLB035);福建省社会科学基金(FJ2020B088)
- DOI：10.12263/DZXB.20230082
  中图分类号： TP391.9;
- 收稿：2023-01-30，
  
  修回：2023-06-20，
  
  纸质出版：2023-09-25
- 稿件说明：
移动端阅览
李海林,王杰,周文浩等.时间序列复杂网络分析中的可视图方法研究综述[J].电子学报,2023,51(09):2598-2622.

LI Hai-lin,WANG Jie,ZHOU Wen-hao,et al.A Review of Visibility Graph Methods Research in Time Series Complex Network Analysis[J].ACTA ELECTRONICA SINICA,2023,51(09):2598-2622.
李海林,王杰,周文浩等.时间序列复杂网络分析中的可视图方法研究综述[J].电子学报,2023,51(09):2598-2622. DOI： 10.12263/DZXB.20230082.

LI Hai-lin,WANG Jie,ZHOU Wen-hao,et al.A Review of Visibility Graph Methods Research in Time Series Complex Network Analysis[J].ACTA ELECTRONICA SINICA,2023,51(09):2598-2622. DOI： 10.12263/DZXB.20230082.

摘要

可视图是将时间序列转换成复杂网络的重要方法之一，也是连接非线性信号分析和复杂网络之间的全新视角，在经济金融、生物医学、工业工程等领域均应用广泛.可视图的拓扑结构继承了原始时间序列的重要性质，稳定且易于实现，通过可视图网络的相关统计特性，可区分特定时间序列数据下的特定行为.首先本文介绍了可视图方法在时间序列复杂网络分析中的相关研究，并通过必要性与可行性分析，充分说明可视图方法的优势所在.然后本文阐述了经典可视图和水平可视图方法的具体步骤及主要性质，从算法的过程改进、效率提升和可视图应用几个方面对现阶段可视图相关研究进行综述，介绍了众多可视图方法的基本过程，分析了可视图算法的识别抗噪能力和建网效率，并归纳整理了这些可视图方法的主要特性与适用范围.另外，本文复现了目前几种主流可视图算法，并公开相关的算法代码以供参考使用.通过对可视图相关研究的综述分析，可了解现阶段可视图的主要研究方向，为未来相关研究提供思路，并为时间序列复杂网络分析奠定基础.

Abstract

Visibility graph is one of the important methods for converting time series into complex networks

building a bridge between nonlinear signal analysis and complex networks with a new perspective

which is widely used in economic

biomedical

physics and other fields. Visibility graph inherits the dynamics of the original time series

is stable and easy to implement

and can distinguish specific behaviors under specific time series data by the relevant statistical properties of visibility graph. In this paper

we first introduce the application of the visibility graph in the analysis of time series complex networks. The advantages of the visibility graph are fully explained through the necessity and feasibility analysis. Then we describe the steps and main properties of basic visibility graph and horizontal visibility graph

and then review the current research on visibility graph from the following aspects: process improvement of algorithms

efficiency improvement of algorithms and visibility graph applications. We introduce the process of numerous visibility graph methods. We also summarize the main characteristics of these methods

analyze the recognition capability

anti-noise capability and network construction efficiency of visibility graph algorithms. In addition

we implement some algorithms and expose the codes for the general scholars to learn and use. Through the review and analysis of visibility graph related research

we can understand the main research directions of visibility graph at this stage

provide thinking for future related research

and establish the foundation for time series complex network analysis.

关键词

Keywords

references

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