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A novel method for local anomaly detection of time series based on multi entropy fusion

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  • Wang, Gangjin
  • Wei, Daijun
  • Li, Xiangbo
  • Wang, Ningkui

Abstract

Dynamic Shannon entropy, which is fused by Shannon entropy and permuted distribution entropy (PDE), achieves good results in local anomaly recognition of time series. However, the dynamic Shannon entropy performs poorly in identifying various abnormal behaviors of complex signals with noise and chaotic characteristics and periodic background. It also gets unsatisfying results in anomaly detection of signals containing relatively large uncertainty anomaly information. Deng entropy, an extended entropy of Shannon entropy, expands the information capacity of Shannon entropy and is more excellent at describing uncertainty and complexity. In this paper, dynamic Deng entropy (DyEd) is proposed by fusing Deng entropy and PDE to identify local anomalies of time series. Six numerical experiments and an empirical application are conducted to illustrate the efficiency of the proposed method. Results show that the proposed method is of great success for signal anomaly detection with periodic backgrounds.

Suggested Citation

  • Wang, Gangjin & Wei, Daijun & Li, Xiangbo & Wang, Ningkui, 2023. "A novel method for local anomaly detection of time series based on multi entropy fusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
  • Handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001486
    DOI: 10.1016/j.physa.2023.128593
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    References listed on IDEAS

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    1. Cui, Huizi & Zhou, Lingge & Li, Yan & Kang, Bingyi, 2022. "Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    3. Andrew Caplin & Mark Dean & John Leahy, 2022. "Rationally Inattentive Behavior: Characterizing and Generalizing Shannon Entropy," Journal of Political Economy, University of Chicago Press, vol. 130(6), pages 1676-1715.
    4. Zhu, Jia & Wei, Daijun, 2021. "Analysis of stock market based on visibility graph and structure entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 576(C).
    5. Dai, Yimei & He, Jiayi & Wu, Yue & Chen, Shijian & Shang, Pengjian, 2019. "Generalized entropy plane based on permutation entropy and distribution entropy analysis for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 217-231.
    6. Chen, Shijian & Shang, Pengjian & Wu, Yue, 2018. "Weighted multiscale Rényi permutation entropy of nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 548-570.
    7. Wei, Daijun & Deng, Xinyang & Zhang, Xiaoge & Deng, Yong & Mahadevan, Sankaran, 2013. "Identifying influential nodes in weighted networks based on evidence theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2564-2575.
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