Modified dynamic programming approach for offline segmentation of long hydrometeorological time series

  • Abdullah Gedikli
  • Hafzullah Aksoy
  • N. Erdem Unal
  • Athanasios Kehagias
Original Paper


For the offline segmentation of long hydrometeological time series, a new algorithm which combines the dynamic programming with the recently introduced remaining cost concept of branch-and-bound approach is developed. The algorithm is called modified dynamic programming (mDP) and segments the time series based on the first-order statistical moment. Experiments are performed to test the algorithm on both real world and artificial time series comprising of hundreds or even thousands of terms. The experiments show that the mDP algorithm produces accurate segmentations in much shorter time than previously proposed segmentation algorithms.


Time series Offline segmentation Change point Dynamic programming Modified dynamic programming Remaining cost concept 



The authors thank the IAHS Secretary General Dr. Pierre Hubert of Université P. & M. Curie, Paris, France, for sharing his software of automatic segmentation algorithm online. The user-friendly version of the algorithms can be supplied to those who show interest and make a request to the authors. This manuscript has been submitted when the second author (H. Aksoy) was working at Leuphana Universität Lüneburg, Campus Suderburg in Germany as an experienced researcher invited by the Alexander von Humboldt Foundation of Germany.


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Abdullah Gedikli
    • 1
  • Hafzullah Aksoy
    • 1
    • 2
  • N. Erdem Unal
    • 1
  • Athanasios Kehagias
    • 3
  1. 1.Department of Civil EngineeringIstanbul Technical UniversityMaslak, IstanbulTurkey
  2. 2.Fakultät III, Umwelt und Technik, Hydrologie und WasserwirtschaftLeuphana Universität LüneburgSuderburgGermany
  3. 3.School of EngineeringAristotle University of ThessalonikiThessalonikiGreece

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