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Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model

Sadra Shadkani Yousef Hemmatzadeh Amirreza Pak Soroush Abolfathi

国际泥沙研究（英文版）2025，Vol.40Issue(4)：573-587,15.

国际泥沙研究（英文版）2025，Vol.40Issue(4)：573-587,15.DOI:10.1016/j.ijsrc.2025.02.004

Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model

Sadra Shadkani ¹Yousef Hemmatzadeh ²Amirreza Pak ²Soroush Abolfathi³

作者信息

1. School of the Environment,University of Windsor,Ontario,Canada
2. Department of Water Engineering,University of Tabriz,Tabriz,Iran
3. School of Engineering,University of Warwick,Coventry CV4 7AL,UK
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摘要

关键词

Suspended sediment/Hybrid model/Long short-term memory(LSTM)/Feed forward neural network(FFNN)/Stochastic gradient descent(SGD)/Radial basis function(RBF)

Key words

Suspended sediment/Hybrid model/Long short-term memory(LSTM)/Feed forward neural network(FFNN)/Stochastic gradient descent(SGD)/Radial basis function(RBF)

引用本文复制引用

Sadra Shadkani,Yousef Hemmatzadeh,Amirreza Pak,Soroush Abolfathi..Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model[J].国际泥沙研究（英文版）,2025,40(4):573-587,15.

基金项目

The authors would like to thank The Scientific Computing Research Technology Platform at the University of Warwick for the computational resources allocated to this study.SA acknowledges support from the Natural Environmental Research Council(NE/S007350/1). （NE/S007350/1）

国际泥沙研究（英文版）

ISSN：1001-6279

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