DocumentCode
3054334
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
fYear
2011
fDate
26-28 July 2011
Firstpage
1648
Lastpage
1650
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-61284-771-9
Type
conf
DOI
10.1109/ICMT.2011.6003277
Filename
6003277
Link To Document