摘要
基于模糊粗糙集理论,提出了一种综合数据挖掘方法,并将其应用于空间负荷预测中。基于规则约简方法提出了循环采样方法,采用数据库知识获取技术按采集的样本属性值将样本聚类,根据聚类中心对连续取值的属性设定模糊值,根据决策属性的包含度对模糊粗糙规则进行筛选,并采用数据库知识获取技术实现了用地类型的转换。算例结果表明该方法简单灵活,可用于短期、中期和长期空间负荷预测中。
According to fuzzy rough set theory, a comprehensive data mining method is proposed and applied in spatial load forecasting （SLF）. Based on rule reduction method a cyclic sampling method is put forward; by means of knowledge discovery in database （KDD） technique and according to the attribute values of acquired samples, the clustering of samples is conducted; according to clustering center, according to the attribute of clustering center to continuous fetching, the fuzzy values are set and based on inclusion degree of decision attributes the fuzzy rough rules are screened, and by means of KDD the conversion of land use type is implemented. Results of calculation examples show that the proposed method is flexible and can be used in shortmedium- and long-term spatial load forecasting.
出处
《电网技术》
EI
CSCD
北大核心
2007年第14期36-40,56,共6页
Power System Technology
关键词
空间负荷预测
数据挖掘
数据库知识获取(KDD)
模糊粗糙集
配电网规划
spatial load forecasting
data mining
knowledge discovery in database （KDD）
fuzzy rough set
distribution network planning
