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Reseach Article

Time Series Representation for Identification of Extremes

by Rajesh Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 14
Year of Publication: 2014
Authors: Rajesh Kumar
10.5120/17075-7515

Rajesh Kumar . Time Series Representation for Identification of Extremes. International Journal of Computer Applications. 97, 14 ( July 2014), 14-19. DOI=10.5120/17075-7515

@article{ 10.5120/17075-7515,
author = { Rajesh Kumar },
title = { Time Series Representation for Identification of Extremes },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 14 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number14/17075-7515/ },
doi = { 10.5120/17075-7515 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:24:06.698007+05:30
%A Rajesh Kumar
%T Time Series Representation for Identification of Extremes
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 14
%P 14-19
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Extracting information from the huge time series is a challenging task. Databases are prepared by keeping in mind the type of information required. Indexing a time series is a difficult task, where shape may not be exact. Finding the minima and maxima of the time series is another difficult job dependent on the expert's subjectivity. In this information age algorithmic trading is the buzz word. For the identification of various patterns, a machine can be made intelligent by embedding some good algorithm in the trading module to identify the various patterns. In this paper an attempt has been made to identify the extremes, where profit probability is maximized.

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Index Terms

Computer Science
Information Sciences

Keywords

SAX time sequence DFT DWT