Time Series Grouping Based on Fuzzy Sets and Fuzzy Sets Type 2

  • Anton RomanovEmail author
  • Irina Perfilieva
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 874)


The contribution is focused on a new method of grouping time series according to their local tendency indicator that is expressed by a linear coefficient of the \(F^1\)-transform. The useful consequence of grouping is an effective procedure of forecasting such that only one time series from a group is forecasted. Our approach for the analysis and forecasting of the time series of software development is used.



The authors acknowledge that the work was supported by the framework of the state task of the Ministry of Education and Science of the Russian Federation No. 2.1182.2017/4.6 “Development of methods and means for automating the production and technological preparation of aggregate-assembly aircraft production in the conditions of a multi-product production program” and RFFI-16-47-732070.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute for Research and Applications of Fuzzy ModelingUniversity of OstravaOstravaCzech Republic

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