Research on Cognitive Mining Method of Ship Formation Behavior Law Based on Knowledge Graph and Fuzzy Association Logic
Hongrun Wang, Tao Wang, Nannan Li, Lin Ding, Tianle Xie · 2023
With the continuous development of sensor and communication technology, the ability to acquire the situation information of naval battle field has been continuously improved, and the importance of accurately understanding and explaining ship formation behavior for military decision-making has been realized. In order to solve the problem of inaccuracy and delay caused by manual analysis of situation information, this paper aims to explore a cognitive mining method of behavior law based on knowledge graph and fuzzy association logic, so as to deeply recognize and mine the target situation information of ship formation. Firstly, based on knowledge graph construction technology, knowledge extraction, knowledge fusion and knowledge processing, the multi-source data of ship formation is structurally represented, and the knowledge graph including ship formation, interception and interference is constructed. Then, the applicability and effectiveness of the fuzzy logic reasoning method in the mining of ship formation behavior law are analyzed by introducing fuzzy correlation logic. Then we study the effect of knowledge graph and fuzzy association logic reasoning on the mining of behavior rules, including association information introduction and fuzzy rule weighting. Finally, based on this method, the law mining and cognitive architecture of ship formation release behavior in chaff are constructed, including the dynamic updating of cognition and mining process and knowledge graph. It is found that the cognition and mining method based on knowledge graph and fuzzy correlation provides a feasible solution for the cognition and mining of ship formation behavior law.