为科学合理、精准地对铁路潜在关键风险源进行定位管控,针对复杂事故链情境下的潜在风险关联推理问题,提出基于事故链情境本体建模的知识推理方法.首先在分析事故链案例情境要素的基础上,解析事故致因机理;其次构建基于本体的事故风险源知识模型,并建立事故风险源知识库;之后基于由知识关联分析获取的风险源关联推理规则,采用Apriori算法对隐患库进行关联分析,并将所得关联规则重新导入事故风险源知识库,以实现知识库的自学习与自更正;最后通过以地点为关键索引的事故链实例分析,验证方法的合理性和有效性,为精细化铁路风险预控提供参考.%In order to positon and control the potential key risk sources of railway scientifically,reasonably and accurately,to deal with the inter-relation reasoning problems of the potential risks in the complex accident chain context,a knowledge reasoning method was proposed based on ontology modeling of accident chain con text.First,the causation mechanism of accident was resolved based on the analysis of the context elements in accident chain cases.Then,the knowledge model of accident and risk sources was built based on the ontology theory,and the knowledge base of accident risk sources was established.Based on the inter-relation reasoning rules of risk sources obtained by knowledge inter-relation analysis.The Apriori algorithm was used to analyze the risk inter-relation from hidden danger data base.The inter-relation rules obtained from the Apriori algo rithm were reimported into the knowledge base of accident and risk sources in order to realize the self-learning and self-correction of the knowledge base.Finally,the method was used to analyze the accident chain cases with the choice of location as the key index.The results proved the rationality and validity of the method,which can provide a reference for the precise railway risk precontrol.
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