Volume 36 Issue 4
Apr.  2010
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Liu Zhongqi, Yuan Xiugan, Fan Yuboet al. Pilot performance evaluation model based on BP neural networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(4): 403-406. (in Chinese)
Citation: Liu Zhongqi, Yuan Xiugan, Fan Yuboet al. Pilot performance evaluation model based on BP neural networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(4): 403-406. (in Chinese)

Pilot performance evaluation model based on BP neural networks

  • Received Date: 23 Apr 2009
  • Publish Date: 30 Apr 2010
  • In order to evaluate pilot performance objectively, back propagation(BP) neural network model of 6-14-3 form in topology with eye movement data was established. Data source of BP neural networks that came from former experiment and random interpolation was divided into training set and test set and normalized. Based on neural networks toolbox in Matlab, hidden layer nodes of BP networks were determined with empirical formula and experimental comparision; BP algorithms in the toolbox were optimized; The training set data and test data were input into model for training and simulation; Pilot performance of the three skill levels was predicated and evaluated. The research shows that pilot performance can be accurately evaluated by setting up BP neural networks model with eye movement data and the evaluation method can provide a reference for flight training.

     

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