电力建设2018，Vol.39Issue(5)：21-27,7.DOI:10.3969/j.issn.1000-7229.2018.05.003
电压暂降事件的频繁模式挖掘与知识推理分析
Frequent Pattern Mining and Knowledge Reasoning of Voltage Sag Events
摘要
Abstract
Large amounts of data for voltage sag events have been accumulated in on-line power quality monitoring. Massive data contains the relationship among the items, which can be used to predict the law of events according to association rules. In this paper,a method is designed to convert feature dimension data in the database of voltage sag events into one-dimensional array. Through a single scan executed on the database,the mode mining of multi-dimensional frequent patterns based on that array greatly improves the computation efficiency. According to the generated rule base, integrated with knowledge reasoning technique,calculating the similarity between the predicted data and the regular data, voltage sag prediction is realized. The proposed method is suitable for event data mining and prediction.关键词
电压暂降事件/频繁模式/电能质量/数据挖掘/推理技术Key words
voltage sag event/frequent pattern/power quality/data mining/reasoning technique分类
信息技术与安全科学引用本文复制引用
田世明,卜凡鹏,齐林海,罗燕..电压暂降事件的频繁模式挖掘与知识推理分析[J].电力建设,2018,39(5):21-27,7.基金项目
国家高技术研究发展计划(863计划)项目(2015AA050203) （863计划）
国家电网公司科技项目(52094016000A)This work is supported by National High-Tech Research and Development Plan of China(863 Program)(No.2015AA050203)and State Grid Corporation of China Research Program(No.52094016000A). （52094016000A）
