considering the importance of cd and u as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the eshtehard region in iran by means of a developed artificial neural network (ann) model. the forward selection (fs) method is used to select the input variables and develop hybrid models by ann. from 45 input candidates, 13 and 14 ...

in this study, a three–layer artificial neural network (ann) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. a total of 455 data points were collected from 13 data sources to develop the ann model. superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of t...

because of high cost of drilling and analysis of samples, it needs to predict gold and silvers based on pathfinder such as as, sb, cd, pb and zn and decrease the cost and time exploration project implementation. in this paper, the model based on a multilayer perceptron artificial neural network (mlp-ann) optimized by invasive weed optimization algorithm (iwo) to predict of gold and silver in za...

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...

artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...

in this work, artificial neural network (ann) has been employed to propose a practical model forpredicting the surface tension of multi-component mixtures. in order to develop a reliable modelbased on the ann, a comprehensive experimental data set including 15 ternary liquid mixtures atdifferent temperatures was employed. these systems consist of 777 data points generally containinghydrocarbon ...

simulation of groundwater fluctuations plays a crucial role in management of watersheds and water demand balancing. recently, wavelet analysis has been used widely in time series decomposition and coupling with neural networks for hydrological modeling. in this paper, the ability of the wavelet-dynamic artificial neural networks (w-ann) model was applied in forecasting one-month-ahead of ground...

background: as bremsstrahlung photon beam fluence is important parameter to be known in a photonuclear reaction experiment as the number of produced particle is strongly depends on photon fluence. materials and methods: photon production yield from different thickness of aluminum target has been estimated using artificial neural network (ann) model. target thickness and incoming electron energy...