数据挖掘聚类算法在电力系统中的应用

Application of data mining clustering algorithmn in power system

针对电力系统当前输出数据多、数据应用能力差等问题,提出一种新型的数据挖掘方法。构建改进型数据挖掘聚类算法模型,通过FCM聚类算法模型实现电力系统应用过程中不同状态数据分析、计算与应用;构建回归算法模型,实现分类后数据信息的预测;通过构建电力系统应用模型,将不同的数据信息融合后,实现了多种数据信息的挖掘与应用。实验证明,该研究方法分类能力强、预测精度高,可推广使用。

Based on the problems of the current large quantity of output data from the power system and the poor data application ability,a new data mining method is proposed.This method constructs an improved data mining clustering algorithm model.The data model can realize the data analysis,calculation and application of different states in the application process of the power system through FCM clustering algorithmn model,and builds a regression algorithm model to predict the data information after classification.This method realizes data mining and application by constructing power system application model and fusing various data information.The experiment,this research method has strong classification ability and high prediction accuracy,which can be generalized for use.