Standard

The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network. / Timoshenkova, Yulia; Safiullin, Nikolai.
Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019. ред. / AY Dolganov. Institute of Electrical and Electronics Engineers Inc., 2019. стр. 248-251 8736555 (Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019).

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Harvard

Timoshenkova, Y & Safiullin, N 2019, The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network. в AY Dolganov (ред.), Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019., 8736555, Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019, Institute of Electrical and Electronics Engineers Inc., стр. 248-251, Международная конференция 2019 Ural Symposium on Biomedical Engineering, Radioelectonics and Information Technology (USBEREIT), Yekaterinburg, Российская Федерация, 25/04/2019. https://doi.org/10.1109/USBEREIT.2019.8736555

APA

Timoshenkova, Y., & Safiullin, N. (2019). The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network. в AY. Dolganov (Ред.), Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019 (стр. 248-251). [8736555] (Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT.2019.8736555

Vancouver

Timoshenkova Y, Safiullin N. The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network. в Dolganov AY, Редактор, Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019. Institute of Electrical and Electronics Engineers Inc. 2019. стр. 248-251. 8736555. (Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019). doi: 10.1109/USBEREIT.2019.8736555

Author

Timoshenkova, Yulia ; Safiullin, Nikolai. / The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network. Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019. Редактор / AY Dolganov. Institute of Electrical and Electronics Engineers Inc., 2019. стр. 248-251 (Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019).

BibTeX

@inproceedings{52b8b63dd6294cae8639740185102180,
title = "The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network",
keywords = "artificial neural network, data analysis, solar activity, sunspot numbers, time series forecast",
author = "Yulia Timoshenkova and Nikolai Safiullin",
year = "2019",
month = apr,
day = "1",
doi = "10.1109/USBEREIT.2019.8736555",
language = "English",
series = "Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "248--251",
editor = "AY Dolganov",
booktitle = "Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019",
address = "United States",
note = "2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019 ; Conference date: 25-04-2019 Through 26-04-2019",

}

RIS

TY - GEN

T1 - The Required Number of Sunspot Cycles in the Training Set for a Better Accuracy of the Forecast with Artificial Neural Network

AU - Timoshenkova, Yulia

AU - Safiullin, Nikolai

PY - 2019/4/1

Y1 - 2019/4/1

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=85068610548&partnerID=8YFLogxK

UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=000481645800065

U2 - 10.1109/USBEREIT.2019.8736555

DO - 10.1109/USBEREIT.2019.8736555

M3 - Conference contribution

AN - SCOPUS:85068610548

T3 - Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019

SP - 248

EP - 251

BT - Proceedings - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019

A2 - Dolganov, AY

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2019

Y2 - 25 April 2019 through 26 April 2019

ER -

ID: 10284792