Suspended sediment load modeling using Hydro-Climate variables and Machine learning-Reference-Cited by-同舟云学术

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Suspended sediment load modeling using Hydro-Climate variables and Machine learning

Published:2024-04 Issue: Volume:633 Page:130948
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Aldin Shojaeezadeh Shahab,Al-Wardy Malik^ORCID,Reza Nikoo Mohammad

Publisher

Elsevier BV

Reference66 articles.

1. Median bed-material sediment particle size across rivers in the contiguous US;Abeshu;Earth Syst. Sci. Data,2022

2. On the capability of preprocessing techniques for suspended sediment load prediction using artificial intelligence methods;Ahmadi;Hydrol. Sci. J.,2022

3. Suspended sediment load prediction using long short-term memory neural network;AlDahoul;Sci. Rep.,2021

4. Barr, M. N. 2016. Surface-water quality and suspended-sediment quantity and quality within the Big River basin, southeastern Missouri, 2011-13. US Geological Survey.

5. Distributed sediment yield modelling: importance of initial sediment conditions;Bussi;Environ. Model. Softw.,2014

Cited by 3 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. Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm;Engineering Applications of Computational Fluid Mechanics;2024-08-20

2. Applicability of sediment rating curves: analysis in the state of Rio Grande do Sul;Revista Brasileira de Geografia Física;2024-07-23

3. Suspended sediment load prediction using sparrow search algorithm-based support vector machine model;Scientific Reports;2024-06-05

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