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The Problem of the Anomaly Detection in Time Series Collections for Dynamic Objects

  • S. G. Antipov
  • V. N. Vagin
  • O. L. Morosin
  • M. V. Fomina
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 875)

Abstract

In this paper the approaches to processing temporal data is considered. The problem of the anomaly detection among sets of time series is setting up. The algorithms TS-ADEEP and TS-ADEEP-Multi for anomaly detection in time series sets for the case when the learning set contains examples of several classes are proposed. The method for improving the accuracy of anomaly detection, due to “compression” of these time series is used.

Keywords

Time series Inductive notion formation Exclusion detection Classification 

Notes

Acknowledgment

This work was supported by grants from the Russian Foundation for Basic Research № 15-01-05567, 17-07-00442.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • S. G. Antipov
    • 1
  • V. N. Vagin
    • 1
  • O. L. Morosin
    • 1
  • M. V. Fomina
    • 1
  1. 1.Department of Application MathematicsNational Research University “MPEI”MoscowRussian Federation

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