一种基于本体与关联规则的煤矿安全监控预警模型

A Model of Safety Monitoring and Early Warning for Coal Mine based on Ontology and Association Rules

为了解决煤矿安全监控系统中的可靠性较差、信息管理混乱,以及产生的海量监测数据利用率较低等问题,提出了一种新的安全监控预警模型。利用本体对煤矿安全监控领域的信息进行系统化组织,使其便于共享与重用;利用关联规则技术对海量监测数据进行挖掘,得到大量隐藏的可用于预警的推理规则;将煤矿安全监控本体及推理规则与 Jena 推理机进行绑定形成具有推理机制的安全监控预警模型。利用该模型对实时数据进行推理实验,验证了该模型有效。结果表明,结合了本体与关联规则技术的煤矿安全监控预警模型可有效地整合监控领域信息,并在一定程度上提高了预警的效率和准确率。

In coal mine safety monitoring system, there are many problems, such as poor reliability, information management confusion, low utilization rate of mass monitoring data. In order to solve these problems, a new monitoring and early warning model of coal mine safety is put forward. The model uses the ontology to systematize the information in the field of coal mine safety monitor, so it makes mine knowledge benefit sharing and reusing;then, the association rule is used to mine the mass monitoring data, and a large number of hidden reasoning rules which can be used for early-warning are obtained;finally, the coal mine safety monitoring ontology and reasoning rules are combined with the Jena reasoning machine, a safety monitoring and warning model with reasoning mechanism is formed. The validity of the model is verified by reasoning experiments with real- time data. The results show that combined with ontology and association rules, the coal mine safety monitoring and early warning model effectively integrate information in monitoring field and improve the accuracy of early-warning to some extent.