Online query algorithm of dynamic time sequences based on fast fourier transform

Author

Zichun Zhang ; Yongdan Liu ; Xiaoyun Guo ; Jianhua Zhu

Author_Institution

Sch. of Autom. & Electr. Eng., Beijing Univ. of Sci. & Technol., Beijing, China

Volume

03

fYear

2012

fDate

Oct. 30 2012-Nov. 1 2012

Firstpage

1346

Lastpage

1352

Abstract

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.

Keywords

fast Fourier transforms; pattern matching; query processing; Euclidean distance; batch pattern; dynamic time sequences; fast Fourier transform; feature value prediction; online similarity query algorithm; pattern time sequences; prediction sequences; time sequences real-time analysis; waiting time reduction; Algorithm design and analysis; Euclidean distance; Fast Fourier transforms; Heuristic algorithms; Prediction algorithms; Time measurement; data mining; dynamic time sequences; fast fourier transform; query based on similarity;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-1855-6

Type

conf

DOI

10.1109/CCIS.2012.6664605

Filename

6664605