煤炭工程 ›› 2015, Vol. 47 ›› Issue (5): 139-142.doi: 10.11799/ce201505045

• 工程管理 • 上一篇    下一篇

基于OLAM的煤矿企业安全隐患趋势分析

张大伟   

  1. 中国矿业大学(北京)管理学院
  • 收稿日期:2015-01-15 修回日期:2015-02-16 出版日期:2015-05-11 发布日期:2015-05-20
  • 通讯作者: 张大伟 E-mail:zhangdawei1000@163.com

Analysis of Coal Mine Safety Hidden Danger Trends based on OLAM

  • Received:2015-01-15 Revised:2015-02-16 Online:2015-05-11 Published:2015-05-20

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_DataCube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。

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

Abstract: Hidden danger investigation and governance are the top priority of coal mine enterprise's safety management. With the development of informatization, coal enterprises have accumulated a lot of hidden danger data. How to effectively use these historical data has become a new challenge of current safety informatization construction in coal enterprises. This paper first puts forward the concept of data cube and OLAM architecture, and then proposes Apriori_DataCube algorithm based on the integration of OLAP drill function and inter-dimensional association rule. Secondly, this paper extends support-confidence framework based on Kulczynski. Finally, this paper empirically analyzes the Xuehu mine hidden historical data provided by Microsoft SQL Server integration service platform, which provides a new way for coal mine enterprise to grasp the hidden danger trends timely and enhance the hidden danger investigation and governance ability.

Key words: mine safety, hidden danger trends, OLAM, drill, inter-dimensional association rule, Kulczynski, SSIS

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