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.
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.
作者
李海林
王杰
周文浩
蔡煜
林伟滨
LI Hai-lin;WANG Jie;ZHOU Wen-hao;CAI Yu;LIN Wei-bin(College of Business Administration,Huaqiao University,Quanzhou,Fujian 362021,China;College of Business,Quanzhou Normal University,Quanzhou,Fujian 362021,China)
出处
《电子学报》
EI
CAS
CSCD
北大核心
2023年第9期2598-2622,共25页
Acta Electronica Sinica
基金
国家自然科学基金(No.71771094)
国家社会科学基金(No.22FGLB035)
福建省社会科学基金(No.FJ2020B088)。
关键词
可视图
时间序列
复杂网络
网络特征
visibility graph
time series
complex network
network feature
