ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Quality assessment of flight training based on BP neural network
Received date: 2017-05-25
Revised date: 2017-06-23
Online published: 2017-06-23
Supported by
The Civil Aviation Joint Funds of the National Naturl Science Foundation of China (U1533127); Sichun Province Science and Technology Support Plan Project (2015GZ0307); Science and Technology Support Plan Project of Civil Aviation Flight University of China(J2014-03);Innovation Team Support Plan Project of Civil Aviation Flight University of China(JG2016-26)
To overcome the existing shortage of the model for flight training assessment, we propose in this paper the method that makes use of pilot physiological signals and flight parameters to construct the evaluation system based on the BP neural network. The influence of the input indexes on the grading result is calculated according to the weight distributions of the trained network. The reliability of this model is tested by analysis of the numerical example. The validation result shows that the result obtained according to the model proposed is consistent with the sample results of expert evaluation. The proposed model can effectively combine pilot physiological signals with flight training parameters to evaluate the quality of pilot training.
YAO Yusheng , XU Kaijun . Quality assessment of flight training based on BP neural network[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017 , 38(S1) : 721513 -721513 . DOI: 10.7527/S1000-6893.2017.721513
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