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  Detecting Plasma Detachment in the Wendelstein 7-X Stellarator Using Machine Learning

Szücs, M., Szepesi, T., Biedermann, C., Cseh, G., Jakubowski, M., Kocsis, G., et al. (2022). Detecting Plasma Detachment in the Wendelstein 7-X Stellarator Using Machine Learning. Applied Sciences, 12(1): 269. doi:10.3390/app12010269.

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szucs_detecting.pdf (Supplementary material), 18MB
 
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https://doi.org/10.3390/app12010269 (Publisher version)
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Open Access
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 Creators:
Szücs, M.1, Author
Szepesi, T.1, Author
Biedermann, C.2, Author           
Cseh, G.1, Author
Jakubowski, M.3, Author           
Kocsis, G.1, Author
König, R.3, Author           
Krause, M.3, Author           
Perseo, V.3, Author           
Puig Sitjes, A.3, Author           
W7-X Team, Max Planck Institute for Plasma Physics, Max Planck Society, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society, ou_2040305              
3Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856286              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Issued
 Pages: 12 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3390/app12010269
 Degree: -

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Project name : Euratom Research and Training Programme 2014-2018 and 2019-2020 – EUROfusion
Grant ID : 633053
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

Source 1

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Title: Applied Sciences
Source Genre: Journal
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Publ. Info: Basel, Schweiz : MDPI
Pages: - Volume / Issue: 12 (1) Sequence Number: 269 Start / End Page: - Identifier: ISSN: 2076-3417
CoNE: https://pure.mpg.de/cone/journals/resource/2076-3417