Timoshenkova, Yuliya Sergeevna

Engineer Researcher, Training and Research Center "Information Security"
Assistant, Training and Research Center "Information Security"
School of Professional and Academic Education

Fuente: Scopus
Se calcula con base en el n.º de publicaciones almacenadas en Pure y citas de Scopus

Resultados de investigaciones por año

Si hizo algún cambio en Pure, pronto podrá verlo aquí.

Huella digital

Profundizar en los temas de investigación en los que Юлия Сергеевна Тимошенкова está activo. Estas etiquetas de temas provienen de las obras de esta persona. Juntos, forma una huella digital única.

5 Perfiles similares

Red

Colaboración externa reciente a nivel de país. Profundice en los detalles haciendo clic en los puntos.

5 Citas
1 Índice h
5 Conference contribution
2 Chapter
2 Article
2 Conference article

The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set
Timoshenkova, Y. & Safiullin, N., may 2020, Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc., p. 452-455 4 p. 9117641. (Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020).
Resultado de la investigación: Conference contribution
Application of data assimilation methods based on Kalman ensemble filters for the Lorenz attractor
Timoshenkova, Y. S., Porshnev, S. V. & Safiullin, N. T., 24 jul 2019, International Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2018. Simos, T. & Tsitouras, C. (eds.). American Institute of Physics Inc., Vol. 2116. 4 p. 390017. (AIP Conference Proceedings; vol. 2116).
Resultado de la investigación: Conference contribution

Acceso abierto
The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network
Timoshenkova, Y. & Safiullin, N., 1 abr 2019, Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019. Dolganov, AY. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 248-251 4 p. 8736555. (Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019).
Resultado de la investigación: Conference contribution
1 Cita (Scopus)
Application of data assimilation algorithms based on Kalman ensemble filters for the lorenz attractor
Timoshenkova, Y. S., Safiullin, N. T. & Porshnev, S. V., 1 ene 2018, En : CEUR Workshop Proceedings. 2274, p. 82-87 6 p.
Resultado de la investigación: Conference article
On the possibility of correction of the forecasting of the Lorenz attractor dynamic characteristics using experimental data and data assimilation
Timoshenkova, Y., Safiullin, N. & Porshnev, S., 26 jul 2018, En : Journal of Physics: Conference Series. 1053, 1, 012004.
Resultado de la investigación: Conference article
1 Cita (Scopus)

Гран-При областного конкурса «Женский облик науки», 2018
Хальясмаа, Александра Ильмаровна (Recipient), Тимошенкова, Юлия Сергеевна (Recipient) & Волкова, Юлия Владимировна (Recipient), 2018
Premio: Honorary degree
Победитель III областного конкурса «Женский облик науки» номинации «Бизнес-леди в науке», 2019
Тимошенкова, Юлия Сергеевна (Recipient), 2019
Premio: Honorary degree

Timoshenkova, Yuliya Sergeevna

Huella digital

Red

Ver detalles

The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set

Application of data assimilation methods based on Kalman ensemble filters for the Lorenz attractor

The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network

Application of data assimilation algorithms based on Kalman ensemble filters for the lorenz attractor

On the possibility of correction of the forecasting of the Lorenz attractor dynamic characteristics using experimental data and data assimilation

Гран-При областного конкурса «Женский облик науки», 2018

Победитель III областного конкурса «Женский облик науки» номинации «Бизнес-леди в науке», 2019

Представители вуза получили новые гранты РФФИ

В конкурсе «Женский облик науки» победили три представительницы вуза