【摘要】 离群数据挖掘是数据挖掘的重要内容 ,针对时序数据进行离群数据挖掘方法的研究。首先通过对时序数据进行离散傅立叶变换将其从时域空间变换到频域空间 ,将时序数据映射为多维空间的点 ,在此基础上 ,提出一种新的基于距离的离群数据挖掘算法。对某钢铁企业电力负荷时序数据进行仿真实验 ,结果表明了算法的有效性更多还原

【Abstract】 The outlier mining method for time series data is investigated. DFT is used to transform the time series data from time domain to frequency domain. The time series data can be mapped into the multidimensional points in multidimensional space. A distance based algorithm is proposed to mine the outliers. The time series data of the electrical load of a steel plant are used for simulation test. The simulation results show the effectiveness of the algorithm.更多还原