ONLINE QUERY ALGORITHM OF DYNAMIC TIME SEQUENCES BASED ON FAST FOURIER TRANSFORM

摘要：

　　An algorithm of online similarity query of dynamic time sequences is proposed as for the need of time sequences real-time analysis.This algorithm uses improved Euclidean Distance as similar measurement,and then evaluates the similar distance between dynamic time sequences and pattern time sequences in a batch pattern using Fast Fourier Transform.In order to shorten waiting time,prediction patterns are used to predict feature value,and accomplish fast response of online query by comparing the similarity between prediction sequences and pattern sequences.Simulation results show that the proposed algorithm can efficiently and correctly solve the online similar query.

关键词： Dynamic time sequences Data mining Fast fourier transform Query based on similarity

作者: Zichun Zhang Yongdan Liu Xiaoyun Guo Jianhua Zhu

作者单位: School of Automation and Electrical Engineering,Beijing University of Science and Technology,Beijing Information Management Department,Shanghai District,Nanjing Political Work College School of Information Science and Technology,Fudan University,Shanghai 200043,China

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 1808-1814

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）