UDC 517.11+519.92+519.246+519.711
1 Kyiv National University of Technologies and Design, Kyiv, Ukraine
 min_14@ukr.net
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FORECASTING OF FUZZY TIME SERIES BASED ON THE CONCEPT
OF NEAREST FSAND TENSOR MODELS OF TIME SERIES
Abstract. Forecasting of fuzzy time series is considered by presenting a standard fuzzy set in the form of a tensor obtained as a result of the tensor product of components, forming a tensor sequence whose last element (the predicted fuzzy set) is calculated as an incomplete tensor (with missing elements). Singular value decomposition of the restored tensor allows obtaining a subset of ordered pairs that is closest (in terms of the F-norm) to the predicted fuzzy set. An example of predicting a fuzzy time series is given.
Keywords: fuzzy set, tensor, missing data, singular value decomposition, F-norm.
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