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Fast segmentation algorithms for long hydrometeorological time series

✍ Scribed by Hafzullah Aksoy; Abdullah Gedikli; N. Erdem Unal; Athanasios Kehagias

Publisher
John Wiley and Sons
Year
2008
Tongue
English
Weight
256 KB
Volume
22
Category
Article
ISSN
0885-6087

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✦ Synopsis

Abstract

A time series with natural or artificially created inhomogeneities can be segmented into parts with different statistical characteristics. In this study, three algorithms are presented for time series segmentation; the first is based on dynamic programming and the second and the thirdβ€”the latter being an improved version of the formerβ€”are based on the branch‐and‐bound approach. The algorithms divide the time series into segments using the first order statistical moment (average). Tested on real world time series of several hundred or even over a thousand terms the algorithms perform segmentation satisfactorily and fast. Copyright Β© 2008 John Wiley & Sons, Ltd.

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