Prediction of bed load via suspended sediment load using soft computing methods
Author:
Publisher
University of Zagreb, Faculty of Science, Department of Geophysics
Subject
Geophysics
Link
http://geofizika-journal.gfz.hr/vol_32/No1/32-1_Pektas_&_Dogan.pdf
Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Assessment of the fraction of bed load concentration towards the sediment transport of a monsoon-dominated river basin of Eastern India;Journal of Geographical Sciences;2023-05
2. Applying the C-Factor of the RUSLE Model to Improve the Prediction of Suspended Sediment Concentration Using Smart Data-Driven Models;Water;2022-09-24
3. Effect of input-target datasets on sediment transport modelling in alluvial rivers using artificial neural network;Hydrological Sciences Journal;2022-01-20
4. Prediction of bedload transport rate using a block combined network structure;Hydrological Sciences Journal;2022-01-02
5. Improving accuracy of SVM for monthly sediment load prediction using Harris hawks optimization;Materials Today: Proceedings;2022
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