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