Non-parametric algorithm of omissions filling in stochastic data | Научно-инновационный портал СФУ

## Non-parametric algorithm of omissions filling in stochastic data

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference: Information Technologies in Business and Industry (ITBI); Novosibirsk State Tech Univ, Novosibirsk, RUSSIA; Novosibirsk State Tech Univ, Novosibirsk, RUSSIA

Год издания: 2019

Идентификатор DOI: 10.1088/1742-6596/1333/3/032038

Аннотация: The paper presents the results of an algorithm for data processing. In the initial data omissions may occur due to different control discreteness of input and output variables. The paper proposes a non-parametric algorithm for filling gaps. The basic idea is to calculate the non-parametric estimate of the regression function from observations obtained from the object. This allows using all available measurements. Numerous computational experiments have shown that the use of the proposed algorithm has improved the quality of the resulting model several times. The algorithm is influenced by such parameters as the total number of omissions in the sample of observations, measurement interference in communication channels, and the type of object. It should be noted that the developed algorithm is universal and does not depend on the type of equation of the object. © Published under licence by IOP Publishing Ltd. The paper presents the results of an algorithm for data processing. In the initial data omissions may occur due to different control discreteness of input and output variables. The paper proposes a non-parametric algorithm for filling gaps. The basic idea is to calculate the non-parametric estimate of the regression function from observations obtained from the object. This allows using all available measurements. Numerous computational experiments have shown that the use of the proposed algorithm has improved the quality of the resulting model several times. The algorithm is influenced by such parameters as the total number of omissions in the sample of observations, measurement interference in communication channels, and the type of object. It should be noted that the developed algorithm is universal and does not depend on the type of equation of the object. © Published under licence by IOP Publishing Ltd.

#### Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1333, Is. 3

Номера страниц: 32038

ISSN журнала: 17426588

Издатель: Institute of Physics Publishing

#### Авторы

• Korneeva A.A. (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia)
• Chzhan E.A. (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia)
• Denisov M.A. (Siberian State Univ Sci & Technol, Krasnoyarskiy Rabochiy Ave 31, Krasnoyarsk 660037, Russia)
• Medvedev A.V. (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia)
• Kukartsev V.V. (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia; Siberian State Univ Sci & Technol, Krasnoyarskiy Rabochiy Ave 31, Krasnoyarsk 660037, Russia)
• Tynchenko V.S. (Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia; Siberian State Univ Sci & Technol, Krasnoyarskiy Rabochiy Ave 31, Krasnoyarsk 660037, Russia)

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