Fuzzy Model Based Intelligent Prediction of Objective Events

  • Sergey Kovalev
  • Andrey Sukhanov
  • Vitêzslav Stýskala
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 423)

Abstract

There are many processes under control. Nowadays all of them undergo through the automation procedure due to the rapid development of information technologies and computing devices. Because of the fact that many tasks of control deal with the elimination of situations, which can cause emergencies, automatic prediction of objective events in process streams becomes the popular problem decided by automation procedure. This work presents the new approach for intelligent analysis of processes represented by time series data. The main aim of our approach is prediction and detection of objective events. The idea of the technique is referred to the mapping of original time series into phase space and construction of the fuzzy prediction clusters of patterns in this phase space. Prediction stage consists of comparison of observed event with the prediction clusters according to the base of fuzzy rules.

Keywords

Time-series prediction models Automation Fuzzy clusters Temporal mapping 

Notes

Acknowledgments

This work was supported by the Russian Foundation for Basic Research (Grants No. 13-07-00183 A, 13-08-12151 ofi_m_RZHD), by SGS, VSB-Technical University of Ostrava, under the grant no. SP2014/110 and partially supported by Grant of SGS No. SP2015/151, VŠB—Technical University of Ostrava, Czech Republic.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sergey Kovalev
    • 1
  • Andrey Sukhanov
    • 1
  • Vitêzslav Stýskala
    • 2
  1. 1.Rostov State Transport UniversityRostov-on-DonRussia
  2. 2.VŠB Technical University of OstravaOstravaCzech Republic

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