The Use of Time Series to Improve the Prediction Reliability of the Statistical Characteristics of a Controlled Parameter

  • Yu. S. SysoevEmail author
  • O. F. Tsuverkalova

Based on the analysis of time series compiled from the values of a controlled parameter, we propose options for constructing vectors (vector-neighbors), close to the starting vector. It is shown that the use of the coordinates of the constructed vector-neighbors in conjunction with the coordinates of the starting vector allows one to increase the sample sizes for determining the statistical characteristics during prediction of parameter drift and to increase the reliability of the estimates of these characteristics.


time series prediction methods parameter drift neighboring vectors 


  1. 1.
    J. Box and G. Jenkins, Analysis of Time Series. Prediction and Control, Mir, Moscow (1974).Google Scholar
  2. 2.
    A. Yu. Loskutov and A. S. Mikhailov, Fundamentals of the Theory of Complex Systems, Institute for Computer Resarch, Moscow–Izhevsk (2007).Google Scholar
  3. 3.
    E. A. Abidova, L. S. Khegai, A. V. Chernov, et al., “Diagnostics of motor-driven armatures using entropy indicators,” Glob. Yad. Bezop., No. 4, 69–77 (2016).Google Scholar
  4. 4.
    Yu. P. Mukha, A. V. Chernov, E. A. Abidova, and L. S. Khegai, “Algorithmization of the processing of diagnostic signals of electrically driven armature with regard to the chaotic components,” Elektr. Nauch. Zh. Inzh. Vestn. Dona, No. 2, 1–10 (2017),, acc. 06.20.2018.
  5. 5.
    Yu. S. Sysoev, A. A. Salnikov, A. V. Chernov, and V. G. Beketov, “Predictive methods for diagnosing NPP technical objects,” Glob. Yad. Bezop., No. 3, 91–101 (2017).Google Scholar
  6. 6.
    Yu. S. Sysoev and N. A. Simakova, “Estimation of the duration of verification intervals of measuring devices by the methods of queuing theory,” Izmer. Tekhn. No. 12, 10–15 (2014)Google Scholar
  7. 7.
    N. S. Piskunov, Differential and Integral Calculus for Higher Technical Educational Institution: Textbook, Nauka, Moscow (1985), Vol. 2.Google Scholar
  8. 8.
    G. Kramer, Mathematical Methods of Statistics, Mir, Moscow (1975).Google Scholar
  9. 9.
    Yu. S. Sysoyev, “Using time series to form intervals of the same type of behavior of object parameters for different prediction methods,” Izmer. Tekhn., No. 2, 8–12 (2018).Google Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Volgodonsk Engineering and Technical InstituteBranch of the National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)VolgodonskRussia

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