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The extraction of knowledge about dependencies time series for the tasks of forecasting

Keywords:

N.G. Yarushkina – Dr. Sci. (Eng.), Professor, head. Information systems, Ulyanovsk state technical University. E-mail: jng@ulstu.ru
T.V. Afanaseva – Dr. Sci. (Eng.), associate professor, Dept. Information systems, Ulyanovsk state technical University. E-mail: tv.afanasjeva@gmail.com
A.A. Romanov – Ph. D. (Eng.), Dept. Information systems, Ulyanovsk state technical University. E-mail: romanov73@gmail.com
I.A. Timina – post-graduate student, Dept. Information systems, Ulyanovsk state technical University. E-mail: i.timina@ulstu.ru


Often financial indicators of the planning of economic activity characterized by a high degree of similarity. Analysis such parameters based on time series analysis. Analysis for identify groups of similar time series of indicators allows to identify relation for each indicator to the important factors. Applying this analysis is reduced prediction time by simplifyingforecast operations and allow to identify groups of similar processes for obtaining information about the factors that grouping these processes. The paper describes an approach for solving the problems of modeling and forecasting economic time series by identifying the degree of dependence based on correlation and degree of similarity time series.
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