Research of Flight Safety and Technical Evaluation

Abstract

Flight safety is the foundation of survival and development of civil aviation transport industry. Aircraft flight safety can be checked by aircraft flight parameters. We discuss a flight technology evaluation method based on flight parameter data. Firstly, data preprocessing is carried out, and the data is reduced by PCA dimension reduction. Then, BP neural network and decision tree model are established to train and test the data set. Neural network algorithm and machine learning algorithm are used for training. The results show that the BP neural network verification set is more accurate. The comparison table between the predicted results and the real results is shown in Table 3. Among the 15 samples, 14 are correct. The prediction accuracy reaches 93%.