In the present study, Computational Fluid Dynamics (CFD) techniques and Artificial Neural Networks (ANN) are used to predict the pressure drop value (Δp ) of Al2O3-water nanofluid in flat tubes. Δp  is predicted taking into account five input variables: tube flattening (H), inlet volumetric flow rate (Qi  ), wall heat flux (qnw  ), nanoparticle volume fraction (Φ) and nanoparticle diameter (dp ...

the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

This study develops a new approach for forecasting shear Strength of concrete beam without stirrups based on the artificial neural networks (ANN). Proposed ANN considers geometric and mechanical properties of cross section and FRP bars, and shear span-depth ratio. The ANN model is constructed from a set of experimental database available in the past literature. Efficiency of the ANN model was c...

In this paper, the authors made their contribution by constructing a model for forecast of average annual net earnings in EU countries. The is based on artificial neural network (ANN) use and needs its creation have presented proposal entry – economic variables that determine earnings. Generally, implementing an policy aimed at preventing stagnation levels can be achieved running sustainable ou...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

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 electr...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...