%0 DATA
%A Chongli, Di
%A Xiaohua, Yang
%A Xiaochao, Wang
%D 2014
%T The denoised series of the six hydrological time series.
%U https://plos.figshare.com/articles/figure/_The_denoised_series_of_the_six_hydrological_time_series_/1134708
%R 10.1371/journal.pone.0104663.g005
%2 https://ndownloader.figshare.com/files/1630214
%K Computational biology
%K computational neuroscience
%K Artificial neural networks
%K neuroscience
%K cognitive science
%K artificial intelligence
%K hydrology
%K surface water
%K Natural resources
%K water resources
%K mathematics
%K Statistics (mathematics)
%K Statistical methods
%K forecasting
%K Time series analysis
%K Mathematical and statistical techniques
%K Mathematical functions
%K Wavelet transforms
%K Simulation and modeling
%K mathematical modeling
%K denoised
%K hydrological
%X This figure gives the denoising result obtained by the EMD-based method (in red color), as a comparison, the denoising result by the wavelet analysis (in blue color) is also given. It shows much better performances of the EMD-based method in denoising.