background : the study examined the implementation of artificial neural network (ann) for the prediction of ammonia nitrogen removal from landfill leachate by ultrasonic process. methods : a three-layer backpropagation neural network was optimized to predict ammonia nitrogen removal from landfill leachate by ultrasonic process. considering the smallest mean square error (mse), the configuration...

  Abstract: In this paper, Artificial Neural Network (ANN) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. The actual input-output data of the system were measured in order to be used for system identification based on root mean square error (RMSE) minimization approach. It was shown that the designed recurrent neural network is able to pr...

This paper focuses on using the numerical finite volume method (FVM) and artificial neural network (ANN) in order to propose a correlation for computing the entrance length of laminar magnetohydrodynamics (MHD) channels flow. In the first step, for different values of the Reynolds (Re) and Hartmann (Ha) numbers (600<ReL increases.

conclusions as we can see the ann outputs values are very close to actual cu concentration, so indicating that predicted values are accurate and the network design is proper and the input variables well suitable for the prediction of cu concentration. background access to safe drinking water is one of the basic human rights and essential for healthy life. concerns about the effects of copper on...

land-use change affects a number natural processes such as soil erosion, sedimentation, flooding and destruction of soil physical and chemical properties. this change of ecosystem causes the degradation of soil quality which eventually leads to a severe decrease in soil fertility. therefore, various aspects of land-use change should be taken into account in national major decision makings. this...

An optimal artificial neural network (ANN) has been developed to predict the Nusselt number of non-Newtonian nanofluids. The resulting ANN is a multi-layer perceptron with two hidden layers consisting of six and nine neurons, respectively. The tangent sigmoid transfer function is the best for both hidden layers and the linear transfer function is the best transfer function for the output layer....

runoff is one of the major components of calculating water resource processes and is the main issue in hydrology. many concept models are used to predict the amount of runoff, which in most cases depend on topographical and hydrological data. conventional models are not appropriate for areas in which there is little hydrological data. changes in runoff are nonlinear, meaning it is time & space ...

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...