Daily suspended sediment estimation using neuro-wavelet models

被引：28
|
作者：
Kisi, Oezguer [1 ]
机构：
[1] Erciyes Univ, Hydraul Div, Dept Civil Engn, Fac Engn, TR-38039 Kayseri, Turkey
来源：
INTERNATIONAL JOURNAL OF EARTH SCIENCES | 2010年 / 99卷 / 06期
关键词：
Suspended sediment load; Neural networks; Neuro-wavelet; Estimation; NETWORK; PREDICTION; FUZZY; DECOMPOSITION; YIELD; ANN;
D O I：
10.1007/s00531-009-0460-2
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
This paper proposes the application of neuro-wavelet technique for modeling daily suspended sediment-discharge relationship. The neuro-wavelet models are obtained by combining two methods, artificial neural networks (ANN) and discrete wavelet transform. The accuracy of the neuro-wavelet and the ANN models is compared with each other in suspended sediment load estimation. The daily streamflow and suspended sediment data from two stations on Tongue River in Montana are used as case studies. The comparison results reveal that the suggested model could increase the estimation accuracy.
引用
收藏
页码：1471 / 1482
页数：12
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