Abstract
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.
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Acknowledgements
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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Romanov, A., Perfilieva, I. (2019). Time Series Grouping Based on Fuzzy Sets and Fuzzy Sets Type 2. In: Abraham, A., Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Third International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’18). IITI'18 2018. Advances in Intelligent Systems and Computing, vol 874. Springer, Cham. https://doi.org/10.1007/978-3-030-01818-4_38
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