Multiscale cross-sample entropy based on visibility graph for quantifying time series irreversibility

被引:0
|
作者
Yin, Yi [1 ,2 ]
Wang, Xi [1 ,2 ]
Wang, Wenjing [1 ,2 ]
Li, Qiang [1 ,2 ]
Shang, Pengjian [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Engn Res Ctr Struct Reliabil & Operat Measurement, Minist Educ, Beijing 100044, Peoples R China
[3] Beijing Jiaotong Univ, Sch Sci, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
Visibility graph (VG); Multiscale cross-sample entropy based on; visibility graph (VGMCSE); Time series irreversibility; Traffic time series; APPROXIMATE ENTROPY; CHAOS;
D O I
10.1016/j.cnsns.2023.107308
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we propose VGMCSE method to obtain multiscale time series irreversibility and gain more information from time irreversibility analysis. The validity of VGMCSE method is illustrated by numerical simulations on synthesized data and then VGMCSE method is applied on traffic time series to give better understanding about the traffic system from the view of time series irreversibility. By means of the VGMCSE planes for all the simulated time series, it can be found that ARFIMA and FGN series are all time reversible, while Logistic map & Henon map are time irreversible. The simulated series can be classified into two groups: (1) ARFIMA & FGN, (2) Logistic map & Henon map by their time series irreversibility. It can be found that the relationship between asynchrony of ingoing degree sequence and outgoing degree sequence for the simulated series with different parameter is consistent with the complexity and autocorrelation behavior in the corresponding definition of the time series. However, it can be revealed that whether the series is long-term correlated or no matter how strong the persistence or anti-persistence is, the ARFIMA and FGN series are all time reversible, indicating time series irreversibility might have no direct connection with long-range dependence and stationarity of series. For the empirical analysis, the traffic time series recorded by detectors can be classified into three groups: (1) detector 2037, 2038, (2) detector 3055, (3) detector 2036, 2040, 3054, 3056, 3057, 4051, 4052, suggesting that there is more similar time irreversible behavior for speed and volume time series recorded by detectors with nearer positions, while the traffic time series of some special locations present different time irreversible behavior and these locations should be paid more attention and enhanced monitoring. VGMCSE method can not only show the asynchrony of ingoing degree sequence and outgoing degree sequence, but also detect the time series irreversibility for time series of complex system. & COPY; 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:21
相关论文
共 50 条
  • [1] Modified multiscale sample entropy and cross-sample entropy based on horizontal visibility graph
    Lin, Guancen
    Lin, Aijing
    [J]. CHAOS SOLITONS & FRACTALS, 2022, 165
  • [2] Modified multiscale cross-sample entropy for complex time series
    Yin, Yi
    Shang, Pengjian
    Feng, Guochen
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2016, 289 : 98 - 110
  • [3] Asymmetric asynchrony of financial time series based on asymmetric multiscale cross-sample entropy
    Yin, Yi
    Shang, Pengjian
    [J]. CHAOS, 2015, 25 (03)
  • [4] Cross-sample entropy of foreign exchange time series
    Liu, Li-Zhi
    Qian, Xi-Yuan
    Lu, Heng-Yao
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2010, 389 (21) : 4785 - 4792
  • [5] Composite Multiscale Partial Cross-Sample Entropy Analysis for Quantifying Intrinsic Similarity of Two Time Series Affected by Common External Factors
    Li, Baogen
    Han, Guosheng
    Jiang, Shan
    Yu, Zuguo
    [J]. ENTROPY, 2020, 22 (09)
  • [6] Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets
    Wu, Yue
    Shang, Pengjian
    Li, Yilong
    [J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2018, 56 : 49 - 61
  • [7] Classifying of financial time series based on multiscale entropy and multiscale time irreversibility
    Xia, Jianan
    Shang, Pengjian
    Wang, Jing
    Shi, Wenbin
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2014, 400 : 151 - 158
  • [8] Time series irreversibility: a visibility graph approach
    Lacasa, L.
    Nunez, A.
    Roldan, E.
    Parrondo, J. M. R.
    Luque, B.
    [J]. EUROPEAN PHYSICAL JOURNAL B, 2012, 85 (06):
  • [9] Time series irreversibility: a visibility graph approach
    L. Lacasa
    A. Nuñez
    É. Roldán
    J. M. R. Parrondo
    B. Luque
    [J]. The European Physical Journal B, 2012, 85
  • [10] Cross-sample entropy estimation for time series analysis: a nonparametric approach
    Ramirez-Parietti, Ignacio
    Contreras-Reyes, Javier E.
    Idrovo-Aguirre, Byron J.
    [J]. NONLINEAR DYNAMICS, 2021, 105 (03) : 2485 - 2508