人工神经网络-遗传算法优化化学镀四元合金工艺

Optimization of Quaternary Alloy Electroless Plating Process by Artificial Neural Network-Genetic Algorithm

利用BP神经网络-遗传算法对化学镀Ni-Fe-Co-P工艺进行寻优。首先利用正交试验表安排一定数量的实验,以构成人工神经网络的训练集。对训练集训练并利用实验数据检验,得到化学镀工艺的人工神经网络模型。最终再利用遗传算法对其进行寻优,以确定最佳的工艺参数。结果表明该方法结果可靠,可以用于实际各种工艺参数的寻优。

BP neural network-genetic algorithm was used for optimization of Ni-Fe-Co-P electroless plating process.First a certain number of experiments were arranged by using orthogonal test table,in order to constitute a training set of artificial neural network.Through training set training and test of experimental data,artificial neural network model of the chemical plating process was obtained.Then its optimization was carried out by the genetic algorithm,in order to determine the optimal process parameters.The results show that the method is reliable,and can be used to optimize actual various process parameters.