Plasma Tomography at GOLEM Tokamak using Neural Network model

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F24%3A00379849" target="_blank" >RIV/68407700:21340/24:00379849 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Plasma Tomography at GOLEM Tokamak using Neural Network model
Original language description
The paper presents an artificial neural network-based model for tomography reconstruction of visible plasma radiation distribution at the GOLEM tokamak. The training dataset is constructed by samples consisting of emissivity phantoms and associated synthetic measurements from a poloidal cross-section of the GOLEM tokamak. To evaluate the performance of the trained model, a phantom test is performed, and the result shows the considerable prediction potential of the proposed model. In addition, the neural network-based model offers a significantly shorter prediction time compared to traditional tomography methods.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 50th EPS Conference on Plasma Physics
ISBN
9798331305239
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
European Physical Society
Place of publication
Mulhouse
Event location
Salamanca
Event date
Jul 8, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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