Open AccessAssessment of the behavior uncertainty level of the short time series
Author(s) -
Liliya Demidova,
М. А. Степанов
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1479/1/012012
Subject(s) - series (stratigraphy) , similarity (geometry) , fuzzy logic , linear regression , time series , regression , mathematics , computer science , econometrics , statistics , artificial intelligence , paleontology , image (mathematics) , biology
The article considers the problem of assessing the level of uncertainty in the behavior of the short time series. The approach to solving this problem, based on the use of the fuzzy linear regression equation with the asymmetric parameters has been proposed. The methods for assessing the level of uncertainty in the behavior of the short time series using the fuzzy similarity measures have been considered. A herewith, the time series which describes the equation of the classical linear regression is used as the standard time series. The presented results of experimental studies confirm the effectiveness of using the proposed approach to assess the level of uncertainty in the behavior of the short time series.