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

Research output: Journal contributionsJournal articlesResearchpeer-review


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

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.

Original languageEnglish
JournalStochastic Environmental Research and Risk Assessment
Issue number5
Pages (from-to)547-557
Number of pages11
Publication statusPublished - 07.2010

    Research areas

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