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Support vector machine-based feature extractor for L/H transitions in JETGonzales, S. ...Support vector machines (SVM) are machine learning tools originally developed in the field of artificial intelligence to perform both classification and regression. In this paper, we show how SVM can ... be used to determine the most relevant quantities to characterize the confinement transition from low to high confinement regimes in tokamak plasmas. A set of 27 signals is used as starting point. The signals are discarded one by one until an optimal number of relevant waveforms is reached, which is the best tradeoff between keeping alimited number of quantities and not loosing essential information. The method has been applied to a database of 749 JET discharges and an additional database of 150 JET discharges has been used to test the results obtained.Source: Proceedings (Iss. 10, Vol. 81, 2010, 10E123-1-10E123-3)Type of material - conference contributionPublish date - 2010Language - englishCOBISS.SI-ID - 25345831
Author
Gonzales, S. |
Lengar, Igor |
Snoj, Luka, 1981- |
Trkov, Andrej
Topics
jedrska fizika
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Gonzales, S. | ![]() |
Lengar, Igor | 19167 |
Snoj, Luka, 1981- | 27819 |
Trkov, Andrej | 08557 |
Source: Personal bibliographies
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