• DOI:10.2166/WST.2007.590
• Corpus ID: 25816385

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

@article{Villez2007ComparisonOT,
  title={Comparison of two wavelet-based tools for data mining of urban water networks time series.},
  author={Kris Villez and Genevi{\`e}ve Pelletier and Christian Rosen and François Anctil and Carl Duchesne and P. A. Vanrolleghem},
  journal={Water science and technology : a journal of the International Association on Water Pollution Research},
  year={2007},
  volume={56 6},
  pages={
          57-64
        }
}

• K. Villez, G. Pelletier, +3 authors P. Vanrolleghem
• Published 1 September 2007
• Computer Science
• Water science and technology : a journal of the International Association on Water Pollution Research

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.