Science Research  Academic Press

Flight Technology Evaluation Based on Flight Parameters

ZiZheng Li 
LiuChen Dai 
YiMing Wang 
HanLin Qin 
JinPing Zhang 
XinRan Yin 
Keywords: Flight safety; flight technology assessment; gradient boosting decision tree;deep learning network.

Abstract

Based on the flight safety, this paper develops a flight technology evaluation method based on the gradient boosting decision tree ( GBDT ) model by collecting and analyzing flight data. This method comprehensively considers flight parameters and provides a more accurate pilot flight technology assessment tool through the analysis of flight records. It is expected to improve the training plan and enhance the technical level of pilots to further improve the safety and sustainable development of air transportation. By introducing the deep learning network structure optimization evaluation method, the flight safety is further enhanced.