NDLI: Segmentation algorithm for long time series analysis

Content Provider	Springer Nature Link
Author	Gedikli, Abdullah Aksoy, Hafzullah Unal, N. Erdem
Copyright Year	2007
Abstract	Time series analysis is an important issue in the earth science-related engineering applications such as hydrology, meteorology and environmetrics. Inconsistency and nonhomogeneity that might arise in a time series yield segments with different statistical characteristics. In this study, an algorithm based on the first order statistical moment (average) of a time series is developed and applied on five time series with length ranging from 84 items to nearly 1,300. Comparison to the existing segmentation algorithms proves the applicability and usefulness of the proposed algorithm in long hydrometeorological and geophysical time series analysis.
Starting Page	291
Ending Page	302
Page Count	12
File Format	PDF
ISSN	14363240
Journal	Stochastic Environmental Research and Risk Assessment
Volume Number	22
Issue Number	3
e-ISSN	14363259
Language	English
Publisher	Springer-Verlag
Publisher Date	2007-03-08
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution Numerical and Computational Methods in Engineering Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences Probability Theory and Stochastic Processes Math. Applications in Geosciences Math. Application in Environmental Science
Content Type	Text
Resource Type	Article
Subject	Environmental Chemistry Environmental Engineering Water Science and Technology Safety, Risk, Reliability and Quality

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