A four-stage hybrid model for hydrological time series forecasting

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on...

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Veröffentlicht in:	PloS one 2014-08, Vol.9 (8), p.e104663-e104663
Hauptverfasser:	Di, Chongli, Yang, Xiaohua, Wang, Xiaochao
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Basis functions Biology and Life Sciences Climate change Complexity Computer and Information Sciences Crude oil prices Data compression Decomposition Earth Sciences Ecology and Environmental Sciences Empirical analysis Ensemble forecasting Forecasting Hydrologic forecasting Hydrologic models Hydrology Hydrology - methods Laboratories Methods Model accuracy Models, Theoretical Neural networks Neural Networks, Computer Noise Noise reduction Physical Sciences Prediction models Radial basis function Rain Research and Analysis Methods Signal processing Stream flow Time Factors Time series Wavelet analysis Wavelet transforms
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