A hybrid methodology for knowledge organization and application of Chinese civil aviation regulations from mission safety support perspective

Safety is one of the most important issues in aviation. Aviation regulations provide significant information pertinent to the safety design and operation of aircraft; however, this information has not been effectively used. It is difficult to precisely identify and obtain the necessary information due to massive and unstructured provisions. In this study, a hybrid methodology is proposed to realize knowledge system construction using Chinese Civil Aviation Regulations as the object of study. To realize structured knowledge organization and intelligent knowledge application for aviation regulations, the hybrid methodology integrates a semantic cohesion model, a knowledge recognition model, a knowledge organization model, and a knowledge application model. A knowledge system of aviation regulations is built using the hybrid methodology comprising all knowledge necessary for aviation safety. The system provides intelligent knowledge support for the safety analysis of aircraft from the perspective of control system, including the accurate positioning of control elements and thorough acquisition of control conditions. Experiments were conducted to confirm the accuracy of the proposed method, and the 56,853 knowledge triples contained in the knowledge system supported its reliability. A few examples of knowledge retrieval are provided, focusing on the interaction processes of socio-technical elements during aircraft missions. It takes only a few seconds to acquire the knowledge required for safety analysis. The examples show how the hybrid methodology and knowledge system can be utilized to increase the efficiency of safety analysis for socio-technical systems while advancing intelligent knowledge applications in the aviation domain.