Conformal Prediction of Disruptions from Scratch: Application to an ITER Scenario

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• 关键词：SVM ; Conformal predictor ; Disruption ; Nuclear fusion
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9653
• 期：1
• 页码：67-74
• 全文大小：268 KB
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  3.Esposito, B., Granucci, G., Nowak, S., Martin-Solis, J.R., Gabellieri, L., Lazzaro, E., et al.: Disruption control on FTU and ASDEX upgrade with ECRH. Nucl. Fusion 49(6), 065014 (2009)CrossRef
  4.Reux, C., Bucalossi, J., Saint-Laurent, F., Gil, C., Moreau, P., Maget, P.: Experimental study of disruption mitigation using massive injection of noble gases on Tore Supra. Nucl. Fusion 50(9), 095006 (2010)CrossRef
  5.Commaux, N., Baylor, L.R., Jernigan, T.C., Hollmann, E.M., Parks, P.B., Humphreys, D.A., et al.: Demonstration of rapid shutdown using large shattered deuterium pellet injection in DIII-D. Nucl. Fusion 50(11), 112001 (2010)CrossRef
  6.Bakhtiari, M., Olynyk, G., Granetz, R., Whyte, D.G., Reinke, M.L., Izzo, V.: Using mixed gases for massive gas injection disruption mitigation on Alcator C-Mod. Nucl. Fusion 51(6), 063007 (2011)CrossRef
  7.Commaux, N., Baylor, L.R., Combs, S.K., Eidietis, N.W., Evans, T.E., Foust, C.R., et al.: Novel rapid shutdown strategies for runaway electron suppression in DIII-D. Nucl. Fusion 51(10), 103001 (2011)CrossRef
  8.Lehnen, M., Alonso, A., Arnoux, G., Baumgarten, N., Bozhenkov, S.A., Brezinsek, S., et al.: Disruption mitigation by massive gas injection in JET. Nucl. Fusion 51(12), 123010 (2011)CrossRef
  9.de Vries, P.C., Johnson, M.F., Segui, I.: Statistical analysis of disruptions in JET. Nucl. Fusion 49(5), 055011 (2009)CrossRef
  10.Vega, J., Dormido-Canto, S., López, J.M., Murari, A., Ramírez, J.M., Moreno, R., et al.: Results of the JET real-time disruption predictor in the ITER-like wall campaigns. Fusion Eng. Des. 88(6–8), 1228–1231 (2013)CrossRef
  11.Dormido-Canto, S., Vega, J., Ramírez, J.M., Murari, A., Moreno, R., López, J.M., et al.: Development of an efficient real-time disruption predictor from scratch on JET and implications for ITER. Nucl. Fusion 53(11), 113001 (2013)CrossRef
  12.Vega, J., Murari, A., Dormido-Canto, S., Moreno, R., Pereira, A., Acero, A.: Adaptive high learning rate probabilistic disruption predictors from scratch for the next generation of tokamaks. Nucl. Fusion 54(12), 123001 (2014)CrossRef
  13.Gammerman, A., Vovk, V., Vapnik, V.: Learning by transduction. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, Wisconsin. 2074112, pp. 148–55. Morgan Kaufmann Publishers Inc. (1998)
  14.Shafer, G., Vovk, V.: A tutorial on conformal prediction. J. Mach. Learn. Res. 9, 371–421 (2008)MathSciNet MATH
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  18.Moreno, R., Vega, J., Dormido-Canto, S., Pereira, A., Murari, A.: Disruption prediction on JET during the ILW experimental campaigns. Fus. Sci. Technol. 69(2) (2016). doi:10.​13182/​FST15-167
  
• 作者单位：Raúl Moreno (17)
  Jesús Vega (18)
  Sebastián Dormido (19)
  JET Contributors (20)
  
  17. Departamento de Teoría de la Señal y Comunicaciones, UC3M, Madrid, Spain
  18. Laboratorio Nacional de Fusión, CIEMAT, Madrid, Spain
  19. Departamento de Informática y Automática, UNED, Madrid, Spain
  20. EUROfusion Consortium, JET, Culham Science Centre, Abingdon, OX14 3DB, UK
  
• 丛书名：Conformal and Probabilistic Prediction with Applications
• ISBN：978-3-319-33395-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9653

文摘

This article shows a conformal prediction application to disruption prediction from scratch. Considering data from ILW experimental campaigns (both hydrogen and deuterium campaigns), a one-layer disruption predictor has been tested from scratch. The results show a relevant improvement where the success rate (rate of disruptions predicted correctly) increases and the false alarm rate (rate of non-disruptive discharges misclassified) decreases, using conformal prediction (CP) rather than conventional methodology from scratch. CP from scratch achieves a success rate of \(100\,\%\) with the first model and only one disruptive discharge.