基于本体构建的列车信息系统分析方法

Analysis on Train Information Using an Ontology Based Modelling Approach

论文在阐述列车信息领域本体构建方法的基础上提出了一种数理逻辑相关性分析模型。作为人工智能应用的基础性研究,该方法通过对本体不同层次节点相互属性进行相关性描述,为节点关系的逻辑推导提供了数学模型。基于该模型构建的本体本身具有知识学习能力,能够适应不同的运营场景和不断变化的应用环境。本论文所提出的本体构建方法适用于各种领域本体,因此,我们希望论文采用的理论模型及方法能够推进大数据应用的相关研究,为故障诊断及维护、生产管理、运营及风险评估等问题的解决方案提供新的思路。

By establishing the ontology in the field of train information, this paper proposes a correlation analysis model based on mathematical logic, which may provide better understand to the semantic web. As a basic research of artificial intelligence applications, this method describes the interrelationships between the attributes of nodes at different levels in the ontology, and provides a mathematical model for the logical reckoning. The ontology established based on this model has its own knowledge-based learning ability and can adapt to changing train environments and even different operating scenarios, which make the ontology establishment method proposed in this paper applicable to various domain ontology. The theoretical models and methods adopted in this thesis could promote the relevant research of big data application and provide new solution for fault diagnosis and maintenance, production management, operation and risk assessment.