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SPAR: set-based piecewise aggregate representation for time series anomaly detection

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References

  1. Zhang Q, Hu Y P, Ji C, et al. Edge computing application: real-time anomaly detection algorithm for sensing data. J Comput Res Dev, 2018, 55: 524–536

    Google Scholar 

  2. Hu Y, Zhan P, Xu Y, et al. Temporal representation learning for time series classification. Neural Comput Appl, 2020, 32: 1–14

    Google Scholar 

  3. Hu Y, Ji C, Zhang Q, et al. A novel multi-resolution representation for time series sensor data analysis. Soft Comput, 2020, 24: 10535–10560

    Article  Google Scholar 

  4. Zhan P, Sun C, Hu Y, et al. Feature-based online representation algorithm for streaming time series similarity search. Int J Patt Recogn Artif Intell, 2020, 34: 2050010

    Article  Google Scholar 

  5. Hu Y, Ren P, Luo W, et al. Multi-resolution representation with recurrent neural networks application for streaming time series in IoT. Comput Netw, 2019, 152: 114–132

    Article  Google Scholar 

  6. Keogh E, Lin J, Fu A W, et al. Finding unusual medical time-series subsequences: algorithms and applications. IEEE Trans Inform Technol Biomed, 2006, 10: 429–439

    Article  Google Scholar 

  7. Keogh E, Chakrabarti K, Pazzani M, et al. Dimensionality reduction for fast similarity search in large time series databases. Knowledge Inf Syst, 2001, 3: 263–286

    Article  Google Scholar 

  8. Ren H, Liao X, Li Z, et al. Anomaly detection using piece-wise aggregate approximation in the amplitude domain. Appl Intell, 2018, 48: 1097–1110

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Key Research Program of China (Grant No. U1936203), Shandong Provincial Natural Science and Foundation (Grant No. ZR2019JQ23), CERNET Innovation Project (Grant No. NGII20190109), and Project of Qingdao Postdoctoral Applied Research.

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Correspondence to Yupeng Hu.

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Zhan, P., Hu, Y., Chen, L. et al. SPAR: set-based piecewise aggregate representation for time series anomaly detection. Sci. China Inf. Sci. 64, 149101 (2021). https://doi.org/10.1007/s11432-020-3021-6

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  • DOI: https://doi.org/10.1007/s11432-020-3021-6

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