Artificial intelligence-based single and hybrid models for prediction of water quality in rivers: A review
The need for accurate predictions of water quality in rivers has encouraged researchers to
develop new methods and to improve the predictive ability of conventional models. In recent …
develop new methods and to improve the predictive ability of conventional models. In recent …
Implementation of hybrid particle swarm optimization-differential evolution algorithms coupled with multi-layer perceptron for suspended sediment load estimation
River suspended sediment load (SSL) estimation is of importance in water resources
engineering and hydrological modeling. In this study, a novel hybrid approach is …
engineering and hydrological modeling. In this study, a novel hybrid approach is …
A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States
Accurate and reliable suspended sediment load (SSL) prediction models are necessary for
planning and management of water resource structures. More recently, soft computing …
planning and management of water resource structures. More recently, soft computing …
Daily suspended sediment load prediction using artificial neural networks and support vector machines
In recent decades, development of artificial intelligence, as a predictor for hydrological
phenomenon, has created a great change in predictions. This paper investigates the …
phenomenon, has created a great change in predictions. This paper investigates the …
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 …
Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches
Interest in semiarid climate forecasting has prominently grown due to risks associated with
above average levels of precipitation amount. Longer-lead forecasts in semiarid watersheds …
above average levels of precipitation amount. Longer-lead forecasts in semiarid watersheds …
Daily suspended sediment concentration simulation using ANN and neuro-fuzzy models
In the present study, artificial neural networks (ANNs), neuro-fuzzy (NF), multi linear
regression (MLR) and conventional sediment rating curve (SRC) models are considered for …
regression (MLR) and conventional sediment rating curve (SRC) models are considered for …
A hybrid double feedforward neural network for suspended sediment load estimation
Estimation of suspended sediment loads (SSL) in rivers is an important issue in water
resources management and planning. This study proposes a hybrid double feedforward …
resources management and planning. This study proposes a hybrid double feedforward …
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 …
[HTML][HTML] Estimating wet soil aggregate stability from easily available properties in a highly mountainous watershed
AA Besalatpour, S Ayoubi, MA Hajabbasi… - Catena, 2013 - Elsevier
A comparison study was carried out with the purpose of verifying when the adaptive neuro-
fuzzy inference system (ANFIS), artificial neural network (ANN), generalized linear model …
fuzzy inference system (ANFIS), artificial neural network (ANN), generalized linear model …