【摘要】 建立了基于径向基函数网络的注塑成型注射压力和熔体温度的预测模型 ,与BP神经网络模型和CAE结果进行了对比。结果表明 ,径向基函数网络在精度、训练速度等方面优于BP网络更多还原

【Abstract】 A radial basis function network model on injection pressure and melt temperature of injection molding is established in this paper The prediction model based on radial basis function network is trained through injection molding CAE data and verified by additional data successfully Another network model based on back propagation network is also trained for comparison The results show that for the problem studied in this paper, the radial basis function network is much better than back propagation network in accuracy and speed of training更多还原