Prediction of daily suspended sediment load using wavelet and neurofuzzy combined model
This study investigated the prediction of suspended sediment load in a gauging station in the USA by neuro-fuzzy, conjunction of wavelet analysis and neuro-fuzzy as well as conventional sediment rating curve models. In the proposed wavelet analysis and neuro-fuzzy model, observed time series of rive...
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Published in | International journal of environmental science and technology (Tehran) Vol. 7; no. 1; pp. 93 - 110 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Iran
Center for Environment and Energy Research and Studies (CEERS)
01.12.2010
Springer-Verlag |
Subjects | |
Online Access | Get full text |
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Summary: | This study investigated the prediction of suspended sediment load in a
gauging station in the USA by neuro-fuzzy, conjunction of wavelet
analysis and neuro-fuzzy as well as conventional sediment rating curve
models. In the proposed wavelet analysis and neuro-fuzzy model,
observed time series of river discharge and suspended sediment load
were decomposed at different scales by wavelet analysis. Then, total
effective time series of discharge and suspended sediment load were
imposed as inputs to the neuro-fuzzy model for prediction of suspended
sediment load in one day ahead. Results showed that the wavelet
analysis and neuro-fuzzy model performance was better in prediction
rather than the neuro-fuzzy and sediment rating curve models. The
wavelet analysis and neuro-fuzzy model produced reasonable predictions
for the extreme values. Furthermore, the cumulative suspended sediment
load estimated by this technique was closer to the actual data than the
others one. Also, the model could be employed to simulate hysteresis
phenomenon, while sediment rating curve method is incapable in this
event. |
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ISSN: | 1735-1472 1735-2630 |
DOI: | 10.1007/BF03326121 |