摘要
国电大渡河流域水电开发有限公司主要负责大渡河流域水电开发及电站运营管理,工作点多、面广、战线长,因此提升安全生产科技化水平至关重要。安全隐患预测研究以历史安全隐患数据为基础,建立安全隐患关键词数据辞典,通过对安全隐患的辨识、分析及应用,选择恰当的空间、时间维度,改进Apriori算法挖掘安全隐患之间的关系,计算隐患之间的因果置信度、支持度和提升度,定量表征不同隐患之间的依存、促进关系,得到新生安全隐患发生的概率。安全隐患预测分析功能已成功上线运行,实现了安全隐患实时预测、分析,有效支持了安全管理决策,为安全生产形势持续稳定提供了坚实保障。
Dadu River Hydropower Development Co.,Ltd.is mainly responsible for the hydropower development and operation management of hydropower stations in Dadu River Basin.As heavy work tasks in hydropower development,it is essential to improve the scientific and technological level of safety production.The research of potential safety hazard prediction is based on historical potential safety hazard data to establish a dictionary of potential safety hazard keyword data.On the basis of identifying,analyzing and applying potential safety hazards,the appropriate spatial and temporal dimensions are chosen,and the relationship between potential safety hazards can be mined through Apriori algorithm to calculate the causal confidence,support and promotion among potential safety hazards,which quantitatively characterizes the dependence and promotion among different potential safety hazards.Finally,the probability of new potential safety hazards will be gotten.The function of prediction and analysis of potential safety hazards has been put into operation in the company,which realizes the real-time prediction and analysis of potential safety hazards,effectively supports safety management decision-making and provides a solid guarantee for the continuous stability of safety production situation.
作者
代鸿元
王勇飞
DAI Hongyuan;WANG Yongfei(Dadu River Hydropower Development Co.,Ltd.,Chengdu 610041,Sichuan,China)
出处
《水力发电》
北大核心
2020年第2期104-108,共5页
Water Power
关键词
安全隐患
预测
APRIORI算法
因果置信度
支持度
potential safety hazard
forecast
Apriori algorithm
causal confidence
support degree