机场安全热点本体建模及智能划分研究

Research on ontology modeling and intelligent level ranking of airport safety hotspots

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 safe operation of airport surface,and classify safety hotspots as per hazard factors,an average conflict rate of airplanes was applied to divide level ranking of safety hotspots into severe,high,middle and low. A domain ontology of an intelligent diagnosis system of airport safety hotspots was built,database records were converted into individuals,then the hotspots model was combined with SWRL diagnosis rules to produce a new ontology model. A case was analyzed by reasoner and suitable prevention measures were recommended finally. The results show that the proposed method can be used to make a diagnosis conforming with actual operating conditions,and has advantages of both ontology and database.