摘要
风电机组在运行过程中会产生大量的机组数据,随着大量数据的积累及数据库的应用,为了有效地利用产生的有用数据,运用粗糙集数据挖掘方法对数据的属性进行简约、决策,发现数据之间的关联规则,为机组高效运行提供条件。仿真结果表明,基于粗糙集数据挖掘方法不仅可以减小特定属性信息提取的工作量,还能在数据分析中发挥决策的优越性。
The rough set data mining methods is used for attribute reduction and decision-making of data obtained from the operating wind turbines in order to discover the associated rules between the data and use it effectively to im- prove the set efficiency. The simulation results demonstrate that rough set data mining method can not only reduce the extraction of specific attribute information, but also exert the superiority of decision-making on data analysis.
出处
《沈阳工程学院学报（自然科学版）》
2014年第3期205-208,共4页
Journal of Shenyang Institute of Engineering:Natural Science
关键词
粗糙集
决策表
属性简约
决策规则
Rough set
Decision table
Attribute Reduction
Decision Rule
