Neural Network Classification of Discontinuities in Space Plasma Parameters

被引：3
|
作者：
Barkhatov, N. A. [1 ]
Revunov, S. E. [1 ]
机构：
[1] Nizhny Novgorod State Pedag Univ, Nizhnii Novgorod 603950, Russia
来源：
GEOMAGNETISM AND AERONOMY | 2010年 / 50卷 / 07期
基金：
俄罗斯基础研究基金会;
关键词：
ORIENTATION; MOTION;
D O I：
10.1134/S001679321007011X
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
The artificial neural network technique is applied to dividing discontinuities in space plasma and magnetic field parameters into classes corresponding to known types of magnetohydrodynamic discontinuities. Parameter discontinuities registered on the WIND spacecraft between 1996 and 1999 are classified using a network of the Kohonen Layer type. An algorithm for determining the orientation of discontinuity surfaces on the basis of one-dimensional observations of solar wind parameter discontinuities on board spacecraft is proposed.
引用
收藏
页码：894 / 904
页数：11
相关论文
共 50 条
  • [21] Selection of appropriate architecture and parameters of neural network for images recognition and classification
    Kukartsev, V. V.
    Mikhalev, A. S.
    Tarasevich, A., V
    Tynchenko, V. S.
    Ogol, A. R.
    Khramkov, V. V.
    INTERNATIONAL SCIENTIFIC CONFERENCE ON APPLIED PHYSICS, INFORMATION TECHNOLOGIES AND ENGINEERING (APITECH-2019), 2019, 1399
  • [22] A novel neural approach to inverse problems with discontinuities (the GMR neural network)
    Cirrincione, G
    Cirrincione, M
    Lu, C
    Van Huffel, S
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4, 2003, : 3106 - 3111
  • [23] A Method to Determine the Parameters of Phase Space Reconstruction Based on the Neural Network
    Liu, Runjie
    Hou, Zhan
    Shen, Jinyuan
    2009 INTERNATIONAL WORKSHOP ON CHAOS-FRACTALS THEORIES AND APPLICATIONS (IWCFTA 2009), 2009, : 281 - 285
  • [24] Prediction of plasma etching using a classification-based neural network
    Kim, B
    Kim, S
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2004, 151 (09) : C585 - C589
  • [25] Use of a neural network to link AFM etch patterns to plasma parameters
    Kim, Bygunwhan
    Kwon, Sanghee
    VACUUM, 2007, 82 (01) : 78 - 83
  • [26] Neural network system for measurement of movement plasma parameters in electrodynamic railgun
    Kirievskij, EV
    2002 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE SYSTEMS, PROCEEDINGS, 2002, : 211 - 212
  • [27] A novel improvement of neural network classification using further division of partition space
    Wang, Lin
    Yang, Bo
    Chen, Zhenxiang
    Abraham, Ajith
    Peng, Lizhi
    BIO-INSPIRED MODELING OF COGNITIVE TASKS, PT 1, PROCEEDINGS, 2007, 4527 : 214 - +
  • [28] A Tensor Space Model-Based Deep Neural Network for Text Classification
    Kim, Han-joon
    Lim, Pureum
    APPLIED SCIENCES-BASEL, 2021, 11 (20):
  • [29] Classification of Cardiac Abnormality using PPG Fiducial Parameters and Probabilistic Neural Network
    Sahoo, Rashmi Rekha
    Ghosh, Sudipta
    Lala, Aniket
    Kundu, Palash Kumar
    2022 IEEE CALCUTTA CONFERENCE, CALCON, 2022, : 49 - 54
  • [30] Soft Fault Classification of Analog Circuits Using Network Parameters and Neural Networks
    A. Kavithamani
    V. Manikandan
    N. Devarajan
    Journal of Electronic Testing, 2013, 29 : 237 - 240
12345