摘要
隐患排查治理工作是煤矿企业安全管理的首要任务,为有效利用隐患历史数据,首先阐述了数据立方体和OLAM体系结构、OLAP钻取功能和维间关联规则挖掘有机融合的方法并提出了Apriori_Data Cube算法,其次以Kulczynski度量扩展了支持度-置信度框架,最后借助微软SSIS对薛湖矿隐患历史数据加以实证分析,为煤矿企业及时掌握隐患趋势、提升隐患排查治理能力提供了新的思路。
Hidden danger investigation and governance are the top priority of safety management in coal mine enterprise. The concept of data cube and OLAM architecture was elaborated, and Apriori DataCube algorithm was proposed based on the integration of OLAP drill function and inter - dimensional association rule. The support - confidence framework was extended based on Kulczynski. The Xuehu mine hidden historical data provided by Microsoft SQL Server integration service platform was empirically analyzed, which provided a new way for coal mine enterprise to grasp the hidden danger trends timely and enhance the hidden danger investigation and governance ability.
出处
《煤炭工程》
北大核心
2015年第5期139-142,共4页
Coal Engineering
关键词
煤矿企业安全
隐患趋势
联机分析挖掘
钻取
维间关联规则
集成服务
mine enterprise safety
trends of hidden danger
OLAM
drill
inter- dimensional association rule
integration services
