Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

1 Citation (Scopus)
Original languageEnglish
Title of host publicationProceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages199-202
Number of pages4
ISBN (Electronic)9781538649466
DOIs
Publication statusPublished - 13 Jun 2018
Event2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018 - Yekaterinburg, Russian Federation
Duration: 6 May 20188 May 2018

Conference

Conference2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018
CountryRussian Federation
CityYekaterinburg
Period06/05/201808/05/2018

Fingerprint

Sunspots
Model Comparison
sunspots
forecasting
Artificial Neural Network
Forecast
Neural networks
Time series
Data Assimilation
assimilation
Forecasting
High Accuracy
Prediction
predictions
Model

Keywords

  • artificial neural network
  • data analysis
  • solar activity
  • sunspot numbers
  • time series forecast

ASJC Scopus subject areas

  • Information Systems
  • Biomedical Engineering
  • Computer Networks and Communications
  • Computer Science Applications
  • Modelling and Simulation
  • Instrumentation
  • Electrical and Electronic Engineering
  • Control and Optimization

Cite this

Safiullin, N., Porshnev, S., & Kleeorin, N. (2018). Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods. In Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018 (pp. 199-202). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT.2018.8384584
Safiullin, Nikolai ; Porshnev, Sergey ; Kleeorin, Nathan. / Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods. Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 199-202
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keywords = "artificial neural network, data analysis, solar activity, sunspot numbers, time series forecast",
author = "Nikolai Safiullin and Sergey Porshnev and Nathan Kleeorin",
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doi = "10.1109/USBEREIT.2018.8384584",
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booktitle = "Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018",
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Safiullin, N, Porshnev, S & Kleeorin, N 2018, Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods. in Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018. Institute of Electrical and Electronics Engineers Inc., pp. 199-202, 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018, Yekaterinburg, Russian Federation, 06/05/2018. https://doi.org/10.1109/USBEREIT.2018.8384584

Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods. / Safiullin, Nikolai; Porshnev, Sergey; Kleeorin, Nathan.

Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 199-202.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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KW - data analysis

KW - solar activity

KW - sunspot numbers

KW - time series forecast

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BT - Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Safiullin N, Porshnev S, Kleeorin N. Monthly sunspot numbers forecast with artificial neural network combined with dynamo model: Comparison with modern methods. In Proceedings - 2018 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 199-202 https://doi.org/10.1109/USBEREIT.2018.8384584