Generally, the euclidean distance and K-means algorithm can be used to clustering the time series, but it is hard to separate the time series with great different variability well.

• 通常可采用欧式距离及K均值算法进行时间序列聚类，但经分析发现单凭此方法还难以实现不同变化趋势的交通流时间序列的有效分离。