Optimization of Electric Pulse Modification Parameters in Al-5%Cu Alloy Using Neural Networks and Genetic Algorithms
Based on the experiments an optimal pattern of the electric pulse modification for Al-5%Cu was investigated using neural networks and genetic algorithms.The input parameters of the artificial neural network(ANN) are the voltage of electric pulse,electric pulse time and temperature of molten alloy.The outputs of the ANN model are the grain size of Al-5%Cu alloy.Based the successfully trained ANN model,genetic algorithms(GA) are used to optimize the input parameters of the model.The good optimization can be obtained through the integrated mode of neural networks and genetic algorithms.