【摘要】 采用试验法来调整并确定注射工艺参数的方法不仅费时费料、效率低下 ,而且由于参数间的相互影响 ,难以得到最合适的参数值。现对人工神经网络技术在注射工艺参数快速确定方面的应用进行了研究 ,在CAE模拟的基础上 ,利用MATLAB下的神经网络工具箱建立了BP网络模型 ,编制了应用程序 ,对参数非线性映射过程进行求解。结果表明 ,人工神经网络技术应用于注射参数的快速确定方面是可行的更多还原

【Abstract】 Using experiments to adjust and determine the injection parameters is not only a waste of time and material, but also difficult to obtain the best values due to the mutual effect of the parameters. A research was made on the application of artificial neural network to quick determination of the injection parameters. On the basis of the CAE simulation, a BP model was built up by using the neural network toolbox of Matlab, and the application program was worked out to acquire the nonlinear mapping output, which shows that the artificial neural network is applicable for quick determination of the injection parameters.更多还原