Comparison of two wavelet-based tools for data mining of urban water networks time series
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/715275
- author
- Villez, K ; Pelletier, G ; Rosén, Christian LU ; Anctil, F ; Duchesne, C and Vanrolleghem, P A
- organization
- publishing date
- 2007
- 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
- pmid:17898444
- 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
- 2016-04-01 16:22:19
- date last changed
- 2022-01-28 19:12:21
@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}},
keywords = {{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}},
doi = {{10.2166/wst.2007.590}},
volume = {{56}},
year = {{2007}},
}