Suspended sediment load prediction using artificial neural network and ant lion optimization algorithm
Suspended sediment load (SSL) estimation is a required exercise in water resource
management. This article proposes the use of hybrid artificial neural network (ANN) models …
management. This article proposes the use of hybrid artificial neural network (ANN) models …
River suspended sediment load prediction based on river discharge information: application of newly developed data mining models
Suspended sediment load (SSL) is one of the essential hydrological processes that affects
river engineering sustainability. Sediment has a major influence on the operation of dams …
river engineering sustainability. Sediment has a major influence on the operation of dams …
Two decades on the artificial intelligence models advancement for modeling river sediment concentration: State-of-the-art
Simulation approaches employed in sediment processes are important for watershed
management and environmental impact assessment. Use of Stochastic models that based …
management and environmental impact assessment. Use of Stochastic models that based …
Evaluation of data driven models for river suspended sediment concentration modeling
Using eight-year data series from hydrometric stations located in Arkansas, Delaware and
Idaho (USA), the ability of artificial neural network (ANN) and support vector regression …
Idaho (USA), the ability of artificial neural network (ANN) and support vector regression …
The potential of hybrid evolutionary fuzzy intelligence model for suspended sediment concentration prediction
Providing a robust and reliable prediction model for suspended sediment concentration
(SSC) is an essential task for several environmental and geomorphology prospective …
(SSC) is an essential task for several environmental and geomorphology prospective …
Random forest, support vector machine, and neural networks to modelling suspended sediment in Tigris River-Baghdad
M Al-Mukhtar - Environmental monitoring and assessment, 2019 - Springer
Suspended sediment is one of the most influential parameters on the water bodies' pollution.
It can carry different pollutants with different concentration through the suspension …
It can carry different pollutants with different concentration through the suspension …
Rainfall-runoff modelling using hydrological connectivity index and artificial neural network approach
The input selection process for data-driven rainfall-runoff models is critical because input
vectors determine the structure of the model and, hence, can influence model results. Here …
vectors determine the structure of the model and, hence, can influence model results. Here …
Prediction of daily suspended sediment load (SSL) using new optimization algorithms and soft computing models
Accurate modeling and prediction of suspended sediment load (SSL) in rivers have an
important role in environmental science and design of engineering structures and are vital …
important role in environmental science and design of engineering structures and are vital …
Suspended sediment load prediction using artificial intelligence techniques: comparison between four state-of-the-art artificial neural network techniques
Accurate prediction of suspended sediment (SS) concentration is a difficult task for water
resource projects. In recent years, methodologies such as artificial intelligence (AI) …
resource projects. In recent years, methodologies such as artificial intelligence (AI) …
Heat tracing of embankment dam leakage: Laboratory experiments and 2D numerical modelling
S Nan, J Ren, F Ni, L Zhang, X He - Journal of Hydrology, 2022 - Elsevier
Recently, the use of heat as a tracer to evaluate the process of leakage in embankment
dams has attracted wide attention. A more accurate flow-heat coupling model of …
dams has attracted wide attention. A more accurate flow-heat coupling model of …