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DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance

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2019
M34_2019_Petnica2.pdf (379.7Kb)
Authors
Vyklyuk, Yaroslav
Radovanović, Milan M.
Malinović-Milićević, Slavica
Contributors
Nina, Aleksandra
Radovanović, Milan
Srećković, Vladimir A.
Conference object (Published version)
Metadata
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Source:
Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts, 2019, 24-25
Publisher:
  • Belgrade : Geographical Institute "Jovan Cvijić" SASA
Note:
  • This conference was held from 10 to 13 May in Petnica Science Centre, City of Valjevo.

Cobiss ID: 275944460

ISBN: 978-86-80029-77-1

[ Google Scholar ]
Handle
https://hdl.handle.net/21.15107/rcub_dais_13404
URI
https://dais.sanu.ac.rs/123456789/13404
Collections
  • ГИ САНУ - Радови истраживача / GI SASA - Researchers' publications
Institution/Community
Географски институт „Јован Цвијић“ САНУ / Geographical Institute Jovan Cvijić SASA
TY  - CONF
AU  - Vyklyuk, Yaroslav
AU  - Radovanović, Milan M.
AU  - Malinović-Milićević, Slavica
PY  - 2019
UR  - https://dais.sanu.ac.rs/123456789/13404
PB  - Belgrade : Geographical Institute "Jovan Cvijić" SASA
C3  - Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts
T1  - DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance
SP  - 24
EP  - 25
UR  - https://hdl.handle.net/21.15107/rcub_dais_13404
ER  - 
@conference{
author = "Vyklyuk, Yaroslav and Radovanović, Milan M. and Malinović-Milićević, Slavica",
year = "2019",
publisher = "Belgrade : Geographical Institute "Jovan Cvijić" SASA",
journal = "Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts",
title = "DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance",
pages = "24-25",
url = "https://hdl.handle.net/21.15107/rcub_dais_13404"
}
Vyklyuk, Y., Radovanović, M. M.,& Malinović-Milićević, S.. (2019). DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance. in Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts
Belgrade : Geographical Institute "Jovan Cvijić" SASA., 24-25.
https://hdl.handle.net/21.15107/rcub_dais_13404
Vyklyuk Y, Radovanović MM, Malinović-Milićević S. DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance. in Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts. 2019;:24-25.
https://hdl.handle.net/21.15107/rcub_dais_13404 .
Vyklyuk, Yaroslav, Radovanović, Milan M., Malinović-Milićević, Slavica, "DEEP Learning LSTM recurrent neural network for consequence forecasting of the solar wind disturbance" in Integrations of satellite and ground-based observations and multi-disciplinarity in research and prediction of different types of hazards in solar system: book of abstracts (2019):24-25,
https://hdl.handle.net/21.15107/rcub_dais_13404 .

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