プラズマ実験解析・制御へのニューラルネットワークの応用  [in Japanese] Applications of Neural Networks to Data Analysis and Control of Fusion Plasma  [in Japanese]

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Abstract

Applications of neural networks to data analysis and control of fusion plasmas are reviewed. First, a brief introduction to the general features of a neural network is presented, where the neural network is considered as a continuous mapping device, a classification device, a statistical processing device, and a time series predicition device. Then, the applications of neural networks to the research field are explained where the problems to be solved are classified a sfitting function, shaping an experimentally obtained spectrum, analyzing equilibrium quantity, prediction, tomography, and control problems. Throughout the article, we restrict ourselves to description of applications of multi-layer neural networks.

Journal

  • Journal of Plasma and Fusion Research

    Journal of Plasma and Fusion Research 78(9), 842-856, 2002-09-25

    The Japan Society of Plasma Science and Nuclear Fusion Research

References:  53

  • <no title>

    BEALE R.

    Neural Computing : An Introduction, 1990

    Cited by (6)

  • <no title>

    ROJAS R.

    Neural Network: A Systematic Introduction, 1996

    Cited by (1)

  • <no title>

    SWINGLER K.

    Applying Neural Networks, A Practical Guide, 1996

    Cited by (4)

  • <no title>

    ROSENBLATT F.

    Psychological Rev. 65, 386, 1958

    Cited by (1)

  • <no title>

    MINSKY M.

    Perceptron - An Introduction to Computational Geometry, 1969

    Cited by (1)

  • <no title>

    AMARI S.

    IEEE Trans. Electron. Comput. EC-16, 279, 1967

    Cited by (1)

  • <no title>

    RUMMELHART D. E.

    Nature(London) 323, 533, 1986

    Cited by (1)

  • <no title>

    FUNAHASHI K.

    Neural Networks 2, 183, 1989

    Cited by (1)

  • <no title>

    HORNIK K.

    Neural Networks 2, 359, 1989

    Cited by (2)

  • <no title>

    CYBENKO G.

    Math. Control Signal Syst 2, 303, 1989

    Cited by (1)

  • <no title>

    WEIGEND A. S.

    Predicting Sunspots and Exchange Rates with Connectionists Networks, Nonlinear Modeling and Forecasting, SFI Studies int the Sciences and Complexity, Proc. XII, 395, 1992

    Cited by (1)

  • <no title>

    VAN MILLIGEN B. Ph

    Phys. Rev. Lett. 75, 3594, 1995

    Cited by (1)

  • <no title>

    MA X. F.

    Nucl. Instrum. Methods Phys. Res. A 449, 366, 2000

    Cited by (1)

  • <no title>

    馬笑峰

    日本応用数理学会論文誌(Trans. JSIAM) 10, 145, 2000

    Cited by (1)

  • <no title>

    LIAQAT A.

    Comput. Phys. Commun. 141, 350, 2001

    Cited by (1)

  • <no title>

    BAKER D. R.

    Plasma Phys. Control. Fusion 36, 109, 1994

    Cited by (1)

  • <no title>

    SVENSSON J.

    Plasma Phys. Control. Fusion 41, 315, 1999

    Cited by (1)

  • <no title>

    LAGIN L.

    Bulletin of the American Physical Society, Division of Plasma Physics Thirty-Third Annual Meeting 36(9), 7T13, 1991

    Cited by (1)

  • <no title>

    LISTER J. B.

    Nucl.Fusion 31, 1291, 1991

    Cited by (2)

  • <no title>

    LAGIN L.

    Proceedings of the 17th Symposium on Fusion Technology 2, 1057, 1993

    Cited by (1)

  • <no title>

    YOSHINO R.

    Fusion Technol. 30, 237, 1996

    Cited by (3)

  • <no title>

    ALBANESE R.

    Fusion Technol. 30, 219, 1996

    Cited by (2)

  • <no title>

    WIJNANDS T.

    Nucl.Fusion 36, 1405, 1996

    Cited by (3)

  • <no title>

    JEON Y. -M.

    Rev. Sci. Instrum. 513, 2001

    Cited by (1)

  • <no title>

    NA Y. -S.

    Rev. Sci. Instrum. 72, 1400, 2001

    Cited by (1)

  • <no title>

    WROBLEWSKI D.

    Rev.Sci.Instrum. 68, 1281, 1997

    Cited by (3)

  • <no title>

    HERNANDEZ J. V.

    Nucl.Fusion 36, 1009, 1996

    Cited by (3)

  • <no title>

    VANNUCCI A.

    Nucl.Fusion 39, 255, 1999

    Cited by (3)

  • <no title>

    SENGUPTA A.

    Nucl. Fusion 40, 1993, 2000

    Cited by (1)

  • <no title>

    WROBLEWSKI D.

    Nucl.Fusion 37, 725, 1997

    Cited by (3)

  • <no title>

    SENGUPTA A.

    Nucl. Fusion 41, 487, 2001

    Cited by (1)

  • <no title>

    DEMETER G.

    Rev. Sci. Instrum. 68, 1438, 1997

    Cited by (1)

  • <no title>

    SANTOS J.

    Rev.Sci.Instrum. 70, 521, 1999

    Cited by (3)

  • <no title>

    SANTOS J.

    Fusion Eng. Des. 48, 119, 2000

    Cited by (1)

  • <no title>

    NUNES F. D.

    Rev. Sci. Instrum 70, 1047, 1999

    Cited by (1)

  • <no title>

    FERRON J. R.

    Proc. of the 14th IEEE/NPSS Symposium on Fusion Engineering 2, 761, 1992

    Cited by (1)

  • <no title>

    LAGIN L.

    Proc. of the 14th IEEE/NPSS Symposium on Fusion Engineering 2, 824, 1992

    Cited by (1)

  • <no title>

    BISHOP C. M.

    Neural Comput. 7, 206, 1995

    Cited by (1)

  • <no title>

    WINDSOR C. G.

    Fusion Technol. 32, 416, 1997

    Cited by (3)

  • <no title>

    ALLEN L.

    Plasma Phys. Control. Fusion 34, 1291, 1992

    Cited by (1)

  • <no title>

    BISHOP C. M.

    Rev. Sci. Instrum. 65, 1803, 1994

    DOI  Cited by (2)

  • A logical calculus of the ideas immanent in nervous activity

    McCULLOCH W. S.

    Bull. Math. Biophys. 5, 115-133, 1943

    DOI  Cited by (119)

  • Artificial neural networks for solving ordinary and partial differential equations

    LAGARIS I. E.

    IEEE Transactions on Neural Networks 9(5), 987-1000, 1998

    DOI  Cited by (2)

  • <no title>

    BISHOP C. M.

    Rev. Sci. Instrum 63, 4772, 1992

    DOI  Cited by (2)

  • <no title>

    BISHOP C. M.

    Roach, Rev. Sci. Instrum. 63,4450, 1992

    DOI  Cited by (2)

  • <no title>

    BISHOP C. M.

    Plasma Phys. Control. Fusion 35, 765, 1993

    DOI  Cited by (1)

  • <no title>

    COCCORESE E.

    Nucl.Fusion 34, 1349, 1994

    DOI  Cited by (2)

  • <no title>

    PAUTASSO G.

    J. Nucl. Mater. 290-293, 1045, 2001

    DOI  Cited by (3)

  • <no title>

    ZEHETBAUER Th

    Fusion Eng. Des. 56-57, 721, 2001

    DOI  Cited by (1)

  • <no title>

    VITELA J. E.

    Plasma Phys. Control. Fusion 40, 295, 1998

    DOI  Cited by (1)

  • <no title>

    TRIBALDOS V.

    Rev. Sci. Instrum. 68, 931, 1997

    DOI  Cited by (2)

  • Optimization of Neural Network Structure for Feedback Control of TRIAM-1M  [in Japanese]

    IYOMASA Atsuhiro , TAKEDA Tatsuoki , NAKAMURA Kazuo , ITOH Satoshi

    Journal of plasma and fusion research 76(9), 911-921, 2000-09-25

    NDL Digital Collections  References (13) Cited by (2)

  • Neural Network Prediction of Plasma Position for Plasma Position Control on TRIAM-1M  [in Japanese]

    IYOMASA Atsuhiro , TAKEDA Tatsuoki , NAKAMURA Kazuo , ITOH Satoshi

    Journal of plasma and fusion research 77(2), 171-181, 2001-02-25

    NDL Digital Collections  References (15) Cited by (1)

Codes

  • NII Article ID (NAID)
    10009629744
  • NII NACSIS-CAT ID (NCID)
    AN10401672
  • Text Lang
    JPN
  • Article Type
    REV
  • ISSN
    09187928
  • NDL Article ID
    6310835
  • NDL Source Classification
    ZM35(科学技術--物理学)
  • NDL Call No.
    Z15-8
  • Data Source
    CJP  NDL  J-STAGE 
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