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Прогнозирование кусочно-стационарных процессов

Authors: Alekseeva, E. Yu.; Besedin, A. A.; Sharov, R. Yu.;

Прогнозирование кусочно-стационарных процессов

Abstract

Рассматриваются дискретные случайные процессы, содержащие параметры, меняющиеся скачкообразно в случайные моменты времени. Для прогнозирования процессов строится фильтр в предположении постоянства параметров. Момент изменения параметров фиксируется при существенном отличии прогнозируемых и наблюдаемых значений процесса. При обнаружении скачка параметры фильтра меняются на начальные. Задача решается в предположении нормальной аппроксимации всех случайных величин и использования линейных приближений нелинейных зависимостей. Имитационное моделирование предложенных алгоритмов показало их работоспособность. Причем, чем больше интервал постоянства параметров, тем точнее определяется момент скачка. И, наоборот, при частом изменении параметров предложенный метод становится неработоспособным (как и любой другой). Consider discrete stochastic processes that contain parameters changing abruptly at random times. For forecasting processes constructed assuming a constant filter parameters. Time of the change of parameters is fixed when the substantial difference predicted and observed values of the process. Upon detection of the jump change the filter options on the initial. The problem is solved under the assumption of normal approximation of random variables and the use of linear approximations of nonlinear modeling dependences. Simulation modeling of the offered algorithms revealed their working capacity. And the more interval of constancy of parameters, the better the time determined the jump. Conversely, if you change the parameters of the proposed method becomes inoperative (or any other). Алексеева Елена Юрьевна, доцент кафедры прикладной математики, Южно-Уральский государственный университет (г. Челябинск); lena.flk@yandex.ru. Беседин Александр Александрович, доцент кафедры прикладной математики, Южно-Уральский государственный университет (г. Челябинск); besedin@prima.susu.ac.ru. Шаров Роман Юрьевич, аспирант кафедры информатики, Южно-Уральский государственный университет (г. Челябинск); romich@is74.ru. E.Yu. Alekseeva, South Ural State University, Chelyabinsk, Russian Federation, lena.flk@yandex.ru, A.A. Besedin, South Ural State University, Chelyabinsk, Russian Federation, besedin@ prima.susu.ac.ru, R.Yu. Sharov, South Ural State University, Chelyabinsk, Russian Federation, romich@is74.ru

Keywords

скачкообразное изменение параметров, прогнозирование, УДК 681.513.685, фильтр Калмана, forecasting, Kalman filter, an abrupt change in the parameters, ГРНТИ 50.43

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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