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The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set. / Timoshenkova, Yulia; Safiullin, Nikolai.
Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. стр. 452-455 9117641 (Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020).

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Harvard

Timoshenkova, Y & Safiullin, N 2020, The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set. в Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020., 9117641, Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020, Institute of Electrical and Electronics Engineers Inc., стр. 452-455, Международная конференция 2020 Ural Symposium on Biomedical Engineering, Radioelectonics and Information Technology (USBEREIT), Yekaterinburg, Российская Федерация, 14/05/2020. https://doi.org/10.1109/USBEREIT48449.2020.9117641

APA

Timoshenkova, Y., & Safiullin, N. (2020). The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set. в Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020 (стр. 452-455). [9117641] (Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT48449.2020.9117641

Vancouver

Timoshenkova Y, Safiullin N. The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set. в Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc. 2020. стр. 452-455. 9117641. (Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020). doi: 10.1109/USBEREIT48449.2020.9117641

Author

Timoshenkova, Yulia ; Safiullin, Nikolai. / The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set. Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. стр. 452-455 (Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020).

BibTeX

@inproceedings{4cb1144301bf45628f99f496b2cf3768,
title = "The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set",
keywords = "artificial neural network, data analysis, solar activity, sunspot numbers, time series forecast",
author = "Yulia Timoshenkova and Nikolai Safiullin",
year = "2020",
month = may,
doi = "10.1109/USBEREIT48449.2020.9117641",
language = "English",
series = "Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "452--455",
booktitle = "Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020",
address = "United States",
note = "2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020 ; Conference date: 14-05-2020 Through 15-05-2020",

}

RIS

TY - GEN

T1 - The Dependence of the Sunspot Forecast Accuracy Using LSTM Networks from Number of Cycles in the Training Set

AU - Timoshenkova, Yulia

AU - Safiullin, Nikolai

PY - 2020/5

Y1 - 2020/5

KW - artificial neural network

KW - data analysis

KW - solar activity

KW - sunspot numbers

KW - time series forecast

UR - http://www.scopus.com/inward/record.url?scp=85089656477&partnerID=8YFLogxK

U2 - 10.1109/USBEREIT48449.2020.9117641

DO - 10.1109/USBEREIT48449.2020.9117641

M3 - Conference contribution

AN - SCOPUS:85089656477

T3 - Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020

SP - 452

EP - 455

BT - Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020

Y2 - 14 May 2020 through 15 May 2020

ER -

ID: 13680793