基于飞行参数的飞行技术评估

ZiZheng Li, LiuChen Dai, YiMing Wang, HanLin Qin, JInPing Zhang, XinRan Yin
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引用次数: 0

摘要

基于飞行安全的考虑,本文通过收集和分析飞行数据,建立了基于梯度提升决策树(GBDT)模型的飞行技术评估方法。该方法综合考虑了飞行参数,通过对飞行记录的分析,为飞行员提供了更为准确的飞行技术评估工具。它有望完善飞行员培训计划,提升飞行员技术水平,进一步提高航空运输的安全性和可持续发展能力。通过引入深度学习网络结构优化评估方法,进一步提高飞行安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flight Technology Evaluation Based on Flight Parameters
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.
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