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

Villez, K; Pelletier, G; Rosén, Christian LU ; Anctil, F; Duchesne, C and Vanrolleghem, P A (2007) In Water Science and Technology 56(6). p.57-64
Abstract
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... (More)
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 (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
B-splines, wavelet analysis, qualitative representation of trends (QRT), urban water networks
in
Water Science and Technology
volume
56
issue
6
pages
57 - 64
publisher
IWA Publishing
external identifiers
  • wos:000253382900007
  • scopus:36048984148
ISSN
0273-1223
DOI
10.2166/wst.2007.590
language
English
LU publication?
yes
id
a8b2bee0-0071-4f0a-bdd5-d4ae6767fc6a (old id 715275)
date added to LUP
2007-12-10 10:48:31
date last changed
2017-01-01 07:03:26
@article{a8b2bee0-0071-4f0a-bdd5-d4ae6767fc6a,
  abstract     = {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},
  author       = {Villez, K and Pelletier, G and Rosén, Christian and Anctil, F and Duchesne, C and Vanrolleghem, P A},
  issn         = {0273-1223},
  keyword      = {B-splines,wavelet analysis,qualitative representation of trends (QRT),urban water networks},
  language     = {eng},
  number       = {6},
  pages        = {57--64},
  publisher    = {IWA Publishing},
  series       = {Water Science and Technology},
  title        = {Comparison of two wavelet-based tools for data mining of urban water networks time series},
  url          = {http://dx.doi.org/10.2166/wst.2007.590},
  volume       = {56},
  year         = {2007},
}