摘要
分析了传统负荷预测方法的缺点,提出了一种基于数据挖掘技术的负荷预测方法.利用决策树算法进行负荷预测,根据预测结果找出负荷不正常点.依靠关联规则算法,对不正常负荷进行修正,从而使预测结果更加精确.
Analyzing the shortcoming of traditional load forecast method, a method of load forecast based on data mining is put forward. Using the decision tree algorithm to make load forecasting, abnormal load data is found among the load forecasting results. This paper relies on association rules algorithm to modify the abnormal load, so that the load forecasting results will be more accurate.
出处
《计算机系统应用》
2014年第12期182-186,共5页
Computer Systems & Applications
关键词
数据挖掘
关联规则
决策树算法
日负荷曲线
data mining
association rule
decision tree algorithm
daily load curve
