Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D

Rea, Cristina; Granetz, Robert S.

doi:10.1080/15361055.2017.1407206

Title: Exploratory Machine Learning Studies for Disruption Prediction Using Large Databases on DIII-D

Journal Article · Wed Feb 21 00:00:00 EST 2018 · Fusion Science and Technology

DOI:https://doi.org/10.1080/15361055.2017.1407206· OSTI ID:1540362

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Massachusetts Institute of Technology Plasma Science and Fusion Center, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

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Research Organization:: General Atomics, San Diego, CA (United States); Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: FC02-04ER54698; SC0014264

OSTI ID:: 1540362

Journal Information:: Fusion Science and Technology, Vol. 74, Issue 1-2; ISSN 1536-1055

Publisher:: American Nuclear Society

Country of Publication:: United States

Language:: English

References (19)

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Support vector machines for disruption prediction and novelty detection at JET Cannas, B.; Delogu, R. S.; Fanni, A. Fusion Engineering and Design, Vol. 82, Issue 5-14 https://doi.org/10.1016/j.fusengdes.2007.07.004	journal	October 2007
A prediction tool for real-time application in the disruption protection system at JET Cannas, B.; Fanni, A.; Sonato, P. Nuclear Fusion, Vol. 47, Issue 11 https://doi.org/10.1088/0029-5515/47/11/018	journal	October 2007
Results of the JET real-time disruption predictor in the ITER-like wall campaigns Vega, Jesús; Dormido-Canto, Sebastián; López, Juan M. Fusion Engineering and Design, Vol. 88, Issue 6-8 https://doi.org/10.1016/j.fusengdes.2013.03.003	journal	October 2013
Statistical analysis of disruptions in JET de Vries, P. C.; Johnson, M. F.; Segui, I. Nuclear Fusion, Vol. 49, Issue 5 https://doi.org/10.1088/0029-5515/49/5/055011	journal	April 2009
Detection of disruptions in the high- β spherical torus NSTX Gerhardt, S. P.; Darrow, D. S.; Bell, R. E. Nuclear Fusion, Vol. 53, Issue 6 https://doi.org/10.1088/0029-5515/53/6/063021	journal	May 2013
Reconstruction of current profile parameters and plasma shapes in tokamaks Lao, L. L.; St. John, H.; Stambaugh, R. D. Nuclear Fusion, Vol. 25, Issue 11 https://doi.org/10.1088/0029-5515/25/11/007	journal	November 1985
Real time equilibrium reconstruction for tokamak discharge control Ferron, J. R.; Walker, M. L.; Lao, L. L. Nuclear Fusion, Vol. 38, Issue 7 https://doi.org/10.1088/0029-5515/38/7/308	journal	July 1998
MDS plus data acquisition system Stillerman, J. A.; Fredian, T. W.; Klare, K. A. Review of Scientific Instruments, Vol. 68, Issue 1 https://doi.org/10.1063/1.1147719	journal	January 1997
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance Dormann, Carsten F.; Elith, Jane; Bacher, Sven Ecography, Vol. 36, Issue 1 https://doi.org/10.1111/j.1600-0587.2012.07348.x	journal	May 2012
Integrated modeling applications for tokamak experiments with OMFIT Meneghini, O.; Smith, S. P.; Lao, L. L. Nuclear Fusion, Vol. 55, Issue 8 https://doi.org/10.1088/0029-5515/55/8/083008	journal	July 2015
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Prototype of an adaptive disruption predictor for JET based on fuzzy logic and regression trees Murari, A.; Vagliasindi, G.; Arena, P. Nuclear Fusion, Vol. 48, Issue 3 https://doi.org/10.1088/0029-5515/48/3/035010	journal	February 2008
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