Optimizing sediment transport models by using the Monte Carlo simulation and deep neural network (DNN): A case study of the Riba-Roja reservoir-Reference-Cited by-同舟云学术

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Optimizing sediment transport models by using the Monte Carlo simulation and deep neural network (DNN): A case study of the Riba-Roja reservoir

Published:2024-04 Issue: Volume:175 Page:105979
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Dehghan-Souraki Danial^ORCID,López-Gómez David,Bladé-Castellet Ernest,Larese Antonia^ORCID,Sanz-Ramos Marcos

Publisher

Elsevier BV

Reference61 articles.

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

2. Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data;Alp;Environ. Model. Software,2007

3. Erosion rates of cohesive soils;Ariathurai;J. Hydraul. Div.,1978

4. State of the art of reservoir sedimentation management in Spain;Avendaño,2000

5. Determination of sediment accumulation volume and its deposition in the Khachen reservoir;Baljyan;Adv. Mater. Res.,2014

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

2. Extension of Iber for Simulating Non–Newtonian Shallow Flows: Mine-Tailings Spill Propagation Modelling;Water;2024-07-18

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