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为保障场面运行安全,将机场安全热点按致险因素归类,并根据航班日均冲突架次率划分为轻度、中度、高度及重度4个危险等级。提出机场安全热点智能诊断系统的领域本体,首先用本体实例形式表示数据库记录信息,进而结合热点本体模型以及热点诊断本体和语义Web规则语言(SWRL)规则,构成一个新的本体模型。最后,应用推理机分析实际案例,并得出适宜的缓解措施。结果表明,采用SWRL规则推理技术能够得到与实际运行情况一致的诊断结论,并兼顾本体与数据库的优点。
In order to ensure the safety of the operation of the scene, airport security hot spots are classified according to risk factors and divided into four levels of mild, moderate, severe and severe according to the daily average collision rate of flights. Firstly, the domain ontology of airport hotspot intelligent diagnosis system is proposed. Firstly, database record information is represented by ontology instance, and then a new ontology model is formed by combining with hot ontology model, Hot Diagnosis Ontology and Semantic Web Rule Language (SWRL) rules. Finally, the application of reasoning machine to analyze the actual case, and draw appropriate mitigation measures. The results show that using SWRL rule reasoning technology can get the diagnosis conclusion consistent with the actual operation, taking into account the advantages of ontology and database.