Research of Time Series Finding Algorithm Based on Artificial Neural Network

Author

Yu, Zhang

Author_Institution

Inst. for Higher Educ., Hebei Univ. of Sci. & Technol., Shijiazhuang, China

Volume

4

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

400

Lastpage

403

Abstract

In this paper, a new method for time-series pattern finding is proposed. The time-series curve is modeled as sequence of straight lines by piecewise linear approximation and the correspondent Arctg(slopes) of the lines are obtained as samples. Classification accuracy of time-series pattern finding algorithm is improved by using artificial neural network (ANN) and hierarchical processing technology. After we analyze experiment result with way of comparing, it prove that classification accuracy of the new time-series pattern finding algorithm is improved.

Keywords

approximation theory; curve fitting; neural nets; pattern classification; piecewise linear techniques; time series; artificial neural network; classification accuracy; correspondent arctg; hierarchical processing technology; piecewise linear approximation; time series finding algorithm; time-series curve; Artificial neural networks; Classification algorithms; Computer science; Data engineering; Data mining; Databases; Educational technology; Management information systems; Neural networks; Pattern matching; Artificial Neural Network (ANN); Hierarchical processing; Key word data mining; classification accuracy; time-series patterns;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.1017

Filename

5171027