ISBN: 978-981-14-4787-7 DOI: 10.18178/wcse.2020.06.064
A Semantic Recognition Method of Radiotelephony Communication for Apron Controller Based on Deep Learning
Abstract— With the rapid development of China's civil aviation industry, the security and efficiency of airport operation is necessary to improve. Apron control transfer has become a trend at the China airport with 10 million throughputs. However, there is lack of specific research on semantic recognition of apron controller's ground air calls. This paper firstly establishes the framework of apron control semantic recognition. Then it analyzes the structure and content characteristics of apron control ground air call. The feature template of key instructions is extracted based on data from Urumqi airport. Finally a deep learning method is used to achieve semantic recognition of apron controller under special circumstances. The simulation results verify the effectiveness of the model
Index Terms— Apron control; Radiotelephony communication; Deep Learning; Semantic Recognition
Yujie Qiao, Lin Zuo, Shiyu Huang, Zhiyuan Shen
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, CHINA
Air Traffic Management Bureau East China Regional, Civil Aviation Administration of China, CHINA
Cite: Yujie Qiao, Lin Zuo, Shiyu Huang, Zhiyuan Shen "A Semantic Recognition Method of Radiotelephony Communication for Apron Controller Based on Deep Learning " Proceedings of 2020 the 10th International Workshop on Computer Science and Engineering (WCSE 2020), pp.435-439 , Shanghai, China, 19-21 June, 2020.