Research on the Application of Big Data in the Field of Aviation Safety

At present, big data has shown great application effect and broad development prospect in many industries. This paper summarizes main applications of big data in the field of aviation safety, and analyzes main scenarios and difficulties that may be faced in further application of big data in the field of aviation safety, including data size and scale, format, error and normalization. In view of the sparse and high-dimensional characteristics of observable variables in aviation safety big data analysis, the L1/2 regularization method is introduced into data dimensionality reduction. A variable selection algorithm is designed and verified by a case. Simulation results show that the algorithm designed can mine effective variables with high correlation to aviation safety result. Suggestions for development of big data in the field of aviation safety are put forward from the aspects of institutional mechanism construction, basic theory research, professional personnel training, database construction, etc., which has certain reference value for application and development of big data in the field of aviation safety.