TIME SERIES STRUCTURE ANALYSIS OF THE NUMBER OF LAW CASES
https://doi.org/10.34822/1999-7604-2022-4-37-48
Abstract
The study analyzes the time series of the number of new cases in the administrative courts of the Russian Federation using two methods of time series grouping according to the chaotic, stochastic, and regular structure. The first model is based on the entropy‒complexity plane, the second one is presented by the attribute‒object graph. As a result, four groups of time series were derived: regular, regular-chaotic, purely chaotic, and chaotic-stochastic. Most of the series turned out to be chaotic-stochastic, which is common for real systems. Each group of time series is assigned with a suitable prediction algorithm. For example, algo-rithms of nonlinear dynamics can be used for chaotic series, and models based on stochastic processes can be used for strongly stochastic series.
About the Authors
V. A. Gromov
National Research University Higher School of Economics, Moscow
Russian Federation
Russian Federation
Doctor of Sciences (Physics and Mathematics), Professor
E-mail: stroller@rambler.ru
P. P. Lukyanchenko
National Research University Higher School of Economics, Moscow
Russian Federation
Russian Federation
Senior Lecturer
E-mail: lukianchenko.pierre@gmail.com
Yu. N. Beschastnov
National Research University Higher School of Economics, Moscow
Russian Federation
Russian Federation
Research Assistant
E-mail: y.beschastnov@mail.ru
K. K. Tomashchuk
National Research University Higher School of Economics, Moscow
Russian Federation
Russian Federation
Research Assistant
E-mail: korneytomashchuk@yandex.ru
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Review
For citations:
Gromov V.A., Lukyanchenko P.P., Beschastnov Yu.N., Tomashchuk K.K. TIME SERIES STRUCTURE ANALYSIS OF THE NUMBER OF LAW CASES. Proceedings in Cybernetics. 2022;(4 (48)):37-48. (In Russ.) https://doi.org/10.34822/1999-7604-2022-4-37-48
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