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...

The difficulty in gas price forecasting has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting gas prices however, all of the existing models of prediction cannot meet practical needs. In this paper, a novel hybrid intelligent framework is developed by applying a systematic integration of GMDH neural n...

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 the present study, the effective parameters of water-Al2O3 nanofluid flowing in flat tubes are investigated using the EFAST Sensitivity Analysis (SA) method. The SA is performed using GMDH type artificial neural networks (ANN) which are based on validated numerical data of two phase modeling of nanofluid flow in flat tubes. There are five design variables namely: tube flattening (H), flow ra...

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...

Accurate prediction of suspended sediment (SS) concentration is a difficult task for water resource projects. In recent years, methodologies such as artificial intelligence (AI) algorithms have been applied load estimation and these models provided efficient results. The present study investigates the abilities four distinct AI approaches estimating monthly SS in Roodak station on Jajrood River...

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...