DOI:
10.34229/KCA2522-9664.24.1.6
UDC 519.21
1 V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
 knopov1@yahoo.com
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2 Prydniprovska State Academy of Civil Engineering and Architecture, Dnipro, Ukraine
a.s.korkhin@gmail.com
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DETERMINING A PIECEWISE LINEAR TREND OF A NONSTATIONARY
TIME SERIES BASED ON INTELLIGENT DATA ANALYSIS.
I. DESCRIPTION AND JUSTIFICATION OF THE METHOD
Abstract. The problem of identifying the trend of a non-stationary time series is often encountered in various applications. In the article, this trend is proposed to be represented as a linear regression with unknown switching points. Typically, such a regression is built using mathematical programming methods. Moreover, the desired variables are mixed variables, which significantly complicates the problem’s solution. The article proposes a different approach based on data mining using statistical criteria. The algorithms described in the article are used to solve a number of problems, including one practical problem. The calculations showed satisfactory accuracy.
Keywords: linear regression, algorithm, time series, trend, methods, mathematical programming.
full text
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