摘要
基于正交函数系和FCM算法,提出了一种新的时间序列聚类的方法.该方法首先通过一个非线性映射,将长度为n的时间序列映射到L_2空间,然后通过计算函数之间的距离得到时间序列之间的相似度.在此基础上,经过FCM算法实现时间序列的聚类.该方法克服了时间序列的高维数特征为时间序列聚类带来的计算困难.实验结果表明,对高维的时间序列,该方法在压缩率达到80%的情况下,依然具有良好的聚类效果.
Based on the orthogonal function system and FCM algorithm,this paper proposed a method to clustering time series.The time series with length n are first mapped in L_2 space.Then the similarity of series will be obtained by computing the distance among functions.Last,the cluster results of time series have been achieved by FCM algorithm according to these similarities.The advantage of the proposal is to greatly reduce the amount of calculation caused by clustering the high dimensional time series.The experimental results show that the desired cluster results can also be obtained under the case of 80% compressibility.
出处
《系统科学与数学》
CSCD
北大核心
2016年第1期53-60,共8页
Journal of Systems Science and Mathematical Sciences
关键词
时间序列
正交函数系
FCM算法
降维
聚类
Time series
orthogonal function system
FCM algorithm
dimensionality reduction
clustering
