Citation

Feng W. China Saf. Sci. J. 2021; 31(9): 1-7.

Copyright

(Copyright © 2021, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2021.09.001

PMID

unavailable

Abstract

In order to assist police officers to analyze civil aviation security events, deep LSTM model was used to study subject identification of these events. Firstly, multi-modal information of them was presented by establishing a database, and their time series characteristics were extracted. Then, a deep LSTM model was developed to study and predict subjects of security events. The results show that the proposed model can predict subjects more accurately based on time series characteristics of the events, and even in the presence of noise, it can obtain better prediction results. Moreover, related research results have been successfully applied in SZX international airport. © 2021 China Safety Science Journal. All rights reserved.

Language: zh