Pilot performance evaluation model based on BP neural networks

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 comparison; 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.