Comparison of two wavelet-based tools for data mining of urban water networks time series

Research output: Contribution to journalArticle


In this paper, two approaches to data mining of time series have been tested and compared. Both methods are based on the wavelet decomposition of data series and allow the localization of important characteristics of a time series in both the time and frequency domain. The first method is a common method based on the analysis of wavelet power spectra. The second approach is new to the applied field of urban water networks and provides a qualitative description of the data series based on the cubic spline wavelet decomposition of the data. It is shown that wavelet power spectra indicate important and basic characteristics of the data but fail to provide detailed information of the underlying phenomena. In contrast, the second method allows the extraction of more and more detailed information that is important in a context of process monitoring and diagnosis


  • K Villez
  • G Pelletier
  • Christian Rosén
  • F Anctil
  • C Duchesne
  • P A Vanrolleghem
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Other Electrical Engineering, Electronic Engineering, Information Engineering


  • B-splines, wavelet analysis, qualitative representation of trends (QRT), urban water networks
Original languageEnglish
Pages (from-to)57-64
JournalWater Science and Technology
Issue number6
Publication statusPublished - 2007
Publication categoryResearch

Related research output

K Villez, G Pelletier, Christian Rosén, F Anctil, C Duchesne & V A Vanrolleghem, 2007.

Research output: Contribution to conferencePaper, not in proceeding

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