Abstract

AbstractWavelet transforms are combined with predictive methods to develop prediction approaches so that the prediction accuracy can be improved in hydrologic predictions. Although the wavelet transform generates several subseries that show similar characteristics, the predictive method is used to develop the model using those subseries. There are several examples of these kinds of combined models, such as wavelet–multilayer perceptron (MP), wavelet fuzzy, wavelet autoregressive, and so forth. Generally, discrete wavelet transformation is used in combined models rather than continuous wavelet transform for unexplained reasons. As a result, in this study emphasis was placed on the comparison of the continuous wavelet–multilayer perceptron (CWT-MP) and discrete wavelet–multilayer perceptron (DWT-MP) models, which were also compared with the stand-alone MP model. Daily precipitation time series from two stations were used in the model development and comparison process. The current precipitation values were ...

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