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Volume 27 Issue 6
Jun.  2001
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Journal of Beijing University of Aeronautics and Astronautics  > 2001  >  27(6): 636-639.
WANG Shu-ming, XIA Guo-ping. Method of Flying Dynamic Real-Time Forecast Based on BP Neural Network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2001, 27(6): 636-639. (in Chinese)
Citation: WANG Shu-ming, XIA Guo-ping. Method of Flying Dynamic Real-Time Forecast Based on BP Neural Network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2001, 27(6): 636-639. (in Chinese)
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Method of Flying Dynamic Real-Time Forecast Based on BP Neural Network

  • Beijing University of Aeronautics and Astronautics, School of Management

  • Received Date: 21 Mar 2000
  • Publish Date: 30 Jun 2001
    Abstract
  • The disadvantages of the traditional BP neural network include low speed of convergence, high sensitivity and indefinite layers, etc. This paper develops a new BP network model, which can improve the quality of the real time and precision, and applies the developed BP network model to the dynamic forecast of aircraft track. Owing to the advantages of BP network in the aspects of acquisition, remembrance and self-adaptation, it can make the results of the dynamic forecast more efficient and more precise.

     

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  • [1] 张立明．人工神经网络模型及其应用[M]．上海:复旦大学出版社,1993.165~179. [2] 王文剑．一种输入驱动的BP网络高效学习算法[J]．系统工程理论与实践,2000,1(4):15~19. [3] Parles Alexander G. An accelerated learning algorithm for multilayer perception networds[J]． IEEE Trans on Neural Networks, 1994,5(3):493~495. [4] 李敏生．BP学习算法的改进与应用[J]．北京理工大学学报(自然科学版),1999,6(4):24~27. [5] Medsker R. Hybrid neutral network and expert system[M].Massachusetts:Kluwer Academic Publishers,1994. 58~62. [6] Looney G G. Pattern recognition using neural networks. New York:Oxford University Press, 1997.79~85.
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