The combination of genetic algorithm and neural network approach (GANN) has been developed to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation and GANN correction approach has been applied to evaluate the optical absorption energies of 150 organic molecules. The neural network approach reduces the root-mean-square (r...

There is no established method for accurately predicting how much blood loss has occurred during hemorrhage. In the present study, we examine whether a genetic algorithm neural network (GANN) can predict volume of hemorrhage in an experimental model in rats and we compare its accuracy to stepwise linear regression (SLR). Serial measurements of heart period; diastolic, systolic, and mean blood p...

Butt welding of austenitic stainless steel 304 plates was carried out using an electron beam. Experiments were conducted for various combinations of input process parameters determined according to central composite design. Three input parameters, namely accelerating voltage, beam current, and welding speed were considered during the experiments. The weld-bead parameters, namely bead width and ...

This paper evaluates the usefulness of neural networks in GDP forecasting. It is focused on comparing a neural network model trained with genetic algorithm (GANN) to a backpropagation neural network model, both used to forecast the GDP of Albania. Its forecasting is of particular importance in decision-making issues in the field of economy. The conclusion is that the GANN model achieves higher ...

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This study applies artificial neural networks (ANN) to simulate the soil stress-strain relationship observed in test data from triaxial shear testing of saturated sand. A genetic algorithm is used to obtain an optimal framework for the ANN. The results show that the proposed genetic adaptive neural network (GANN) can effectively model undrained monotonic and cyclic triaxial behaviour of saturat...

In order to predict sports performance more accurately, we investigated the recent algorithms, and proposed a hybrid prediction system based on genetic algorithm and artificial neural network (GANN). This is the first paper using the GANN to predict sport performance. We created a database of 1000 samples by questionnaire and physical test. The dataset was divided into two categories of trainin...

In this study artificial neural networks (ANN) are used to simulate the monotonic and cyclic behaviour of sands observed in laboratory tests on Karlsruhe sand under drained undrained conditions. A genetic algorithm (GA) is obtain an optimal framework for ANN. The results show that proposed adaptive network (GANN) can effectively triaxial saturated isotropic or anisotropic consolidation. GANN al...