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Authors: Konstantinos F. Xylogiannopoulos 1 ; Panagiotis Karampelas 2 and Reda Alhajj 1

Affiliations: 1 University of Calgary, Canada ; 2 Hellenic Air Force Academy, Greece

ISBN: 978-989-758-096-3

Keyword(s): Moving Linear Regression Angle, Linear Regression, Pattern Detection, Trend Detection, Local Extrema, Local Minimum, Local Maximum, Discretization.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Methodologies and Technologies ; Operational Research ; Sensor Networks ; Signal Processing ; Simulation ; Soft Computing

Abstract: Mining, analysis and trend detection in time series is a very important problem for forecasting purposes. Many researchers have developed different methodologies applying techniques from different fields of science in order to perform such analysis. In this paper, we propose a new discretization method that allows the detection of local extrema and trends inside time series. The method uses sliding linear regression of specific time intervals to produce a new time series from the angle of each regression line. The new time series produced allows the detection of local extrema and trends in the original time series. We have conducted several experiments on financial time series in order to discover trends as well as pattern and periodicity detection to forecast future behavior of Dow Jones Industrial Average 30 Index.

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Paper citation in several formats:
Xylogiannopoulos, K.; Karampelas, P. and Alhajj, R. (2015). Discretization Method for the Detection of Local Extrema and Trends in Non-discrete Time Series.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 346-352. DOI: 10.5220/0005401203460352

@conference{iceis15,
author={Konstantinos F. Xylogiannopoulos. and Panagiotis Karampelas. and Reda Alhajj.},
title={Discretization Method for the Detection of Local Extrema and Trends in Non-discrete Time Series},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={346-352},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005401203460352},
isbn={978-989-758-096-3},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Discretization Method for the Detection of Local Extrema and Trends in Non-discrete Time Series
SN - 978-989-758-096-3
AU - Xylogiannopoulos, K.
AU - Karampelas, P.
AU - Alhajj, R.
PY - 2015
SP - 346
EP - 352
DO - 10.5220/0005401203460352

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