CAJ | 학술논문

以电力公司的业务需求为背景，为实现电力设备的状态诊断，以数据挖掘技术中的粗糙集和决策树算法为依据，采用粗糙集和决策树相结合的数据处理模型对电力设备的各属性数据进行了分析处理。综合运用粗糙集和决策树两种数据挖掘算法，通过粗糙集技术进行属性约简，并运用决策树的ID3算法对约简后的数据进行分枝、减枝得到规则集，实现对电力设备工作状态的快速、高效诊断，并根据其工作状态提供决策支持。
이전력공사적업무수구위배경，위실현전력설비적상태진단，이수거알굴기술중적조조집화결책수산법위의거，채용조조집화결책수상결합적수거처리모형대전력설비적각속성수거진행료분석처리。종합운용조조집화결책수량충수거알굴산법，통과조조집기술진행속성약간，병운용결책수적ID3산법대약간후적수거진행분지、감지득도규칙집，실현대전력설비공작상태적쾌속、고효진단，병근거기공작상태제공결책지지。
The system uses the business needs of a power company as the background. For the realization of the state testing of electrical equipment, rough sets and decision tree algorithm belonging to data mining technology is used as the basis. The paper proposes a data processing model combining rough sets with decision tree to realize for power each attribute the data analysis and processing equipment for power each attribute of electrical equipment. Rough sets and decision tree are used in this paper synthetically. Through rough set technology attribute reduction can be realized in this paper. Data which has been reduced is branched and cut branches by the use of the ID3 decision tree algorithm, and then rules in order can be got. At last, the working status of electrical equipment can be diagnosed rapidly and effi-ciently and the decision support is provided according to their work status.