Classifier based on support vector machine for JET plasma configurations

S. Dormido-Canto; G. Farias; J. Vega; R. Dormido; J. Sánchez; N. Duro; H. Vargas; A. Murari

doi:10.1063/1.2972023

Classifier based on support vector machine for JET plasma configurations

S. Dormido-Canto, G. Farias, J. Vega, R. Dormido, J. Sánchez, N. Duro, H. Vargas, A. Murari

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.

Original language	English
Article number	10F326
Journal	Review of Scientific Instruments
Volume	79
Issue number	10
DOIs	https://doi.org/10.1063/1.2972023
State	Published - 2008
Externally published	Yes

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10.1063/1.2972023

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title = "Classifier based on support vector machine for JET plasma configurations",

abstract = "The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.",

author = "S. Dormido-Canto and G. Farias and J. Vega and R. Dormido and J. S{\'a}nchez and N. Duro and H. Vargas and A. Murari",

note = "Funding Information: This work, supported by the European Communities under the contract of Association between EURATOM/CIEMAT, was carried out within the framework of the European Fusion Development Agreement. The views and opinions expressed herein do not necessarily reflect those of the European Commission.",

year = "2008",

doi = "10.1063/1.2972023",

language = "English",

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AU - Dormido-Canto, S.

AU - Farias, G.

AU - Vega, J.

AU - Dormido, R.

AU - Sánchez, J.

AU - Duro, N.

AU - Vargas, H.

AU - Murari, A.

N1 - Funding Information: This work, supported by the European Communities under the contract of Association between EURATOM/CIEMAT, was carried out within the framework of the European Fusion Development Agreement. The views and opinions expressed herein do not necessarily reflect those of the European Commission.

PY - 2008

Y1 - 2008

N2 - The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.

AB - The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.

UR - http://www.scopus.com/inward/record.url?scp=55349146312&partnerID=8YFLogxK

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VL - 79

JO - Review of Scientific Instruments

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ER -

Classifier based on support vector machine for JET plasma configurations

Abstract

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