Deep learning for plasma tomography and disruption prediction from bolometer data
Ferreira, Diogo R. ...
The use of deep learning is facilitating a wide range of data processing tasks in many areas. The analysis of fusion data is no exception since there is a need to process large amounts of data ...collected from the diagnostic systems attached to a fusion device. Fusion data involve images and time series and are a natural candidate for the use of convolutional and recurrent neural networks. In this article, we describe how convolutional neural networks can be used to reconstruct the plasma radiation profile, and we discuss the potential of using RNNs for disruption prediction based on the same input data. Both approaches have been applied at the Joint European Torus (JET) using data from a multichannel diagnostic system. Similar approaches can be applied to other fusion devices and diagnostics.
It was not necessary to add the material to the shelf.
Bibliographic material was successfully added on shelf.
Adding bibliographical material on shelf was not successful.
Material is already on the shelf.
Permalink
URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year
Impact factor
Edition
Category
Classification
JCR
SNIP
JCR
SNIP
JCR
SNIP
JCR
SNIP
Select the library membership card:
DRS,
in which the journal is indexed
Database name
Field
Year
Links to authors' personal bibliographies
Links to information on researchers in the SICRIS system
Subject headings in COBISS General List of Subject Headings
Select pickup location
The material from the parent unit is free. If the material is delivered to the pickup location from another unit, the library may charge you for this service.
PDF
