摘要
SCADA系统调度中心保存了大量的数据,如何有效地利用这些数据进行故障、事故分析处理已成为一个重要的课题。提出改进的关联规则Apriori算法对调度中心的数据进行分析处理,提高事后辅助分析决策能力。首先分析了Apriori算法应用的局限性,然后从数据处理和分层挖掘两方面对传统Apriori算法作了优化。对SCADA系统历史数据库的挖掘结果表明,此算法对加快故障、事故的分析和处理有一定的指导意义。
A great deal of data is saved in the dispatching center of SCADA system. It becomes more and more important that utilize the data to dispose and analyze fault information. The improved association rules Apriori arithmetic is given in this paper, which can enhance the capability of auxiliary analysis after fault. At first the disadvantages of the traditional Apriori arithmetic are described and then the optimized arithmetic about data processing and layer data mining is introduced. The result shows that it provides the guidance to accelerate the analysis and processing of fault and slip by mining the history database of SCADA systems.
出处
《华北电力大学学报（自然科学版）》
CAS
北大核心
2008年第4期27-32,共6页
Journal of North China Electric Power University：Natural Science Edition
基金
西南交通大学科技发展基金资助项目(20071528)
