Title :
Research on daily runoff forecasting model of lake
Author :
Zhang, Rijun ; Wang, Yinghua
Author_Institution :
Coll. of Hydrol. & Water Resources, Hohai Univ., Nanjing, China
Abstract :
Once there were many predicting methods, such as ANN, etc. But these methods are not very precisely. This paper uses wavelet analysis to decompose daily runoff series, then it uses ANFIS to modeling the decomposed series, in the end it combined these series. The result shows that, the prediction accuracy rises a lot, and it is fit to used in daily runoff predict.
Keywords :
fuzzy neural nets; geophysics computing; hydrological techniques; lakes; rivers; ANFIS; adaptive neuro-fuzzy inference systems; daily runoff forecasting model; daily runoff series; decomposed series; lake; predicting method; wavelet analysis; Analytical models; Educational institutions; Predictive models; Time frequency analysis; Wavelet analysis; Wavelet transforms; ANFIS; Wavelet-ANFIS; daily runoff; forecasting model; wavelet analysis;
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
DOI :
10.1109/ICMT.2011.6003277
