UDC 681.3, 681.5
IMPROVING THE EFFICIENCY OF MULTIVARIATE TIME SERIES ANALYSIS
A. N. Kabanov, Ph.D. (Tech.), associate Professor of MIS RSREU, Ryazan, Russia;
orcid.org/0000-0002-7248-0918, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
D. N. Folomkin, senior lecturer of MIS RSREU, Ryazan, Russia;
orcid.org/0000-0002-1648-0374, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
The problem to increase the efficiency of multidimensional time series analysis is considered. The aim of the work is to find solutions to increase the efficiency of multidimensional time series analysis. Several approaches are proposed to optimize the analysis, namely: the use of an operational algorithm for determining the optimal temporal scale factor of spectral decomposition under color noise conditions, clustering of multidimensional time series based on Prim’s algorithm, and obtaining recurrent estimates of the approximation of multidimensional time series on a moving interval.
Key words: multidimensional representation, multidimensional time series, white noise, color noise, clustering, Prim's algorithm, recurrence estimates, moving interval, approximation, decomposition coefficients, time scale factor.