【摘要】 采用改进的BP 网络算法———Levenberg Marquardt算法,建立了固溶态Cu Ni Si Cr合金的时效温度和时间参数关于时效后性能的非线性映射模型。结果表明所建立的BP神经网络模型可对Cu Ni Si Cr合金时效后的性能进行有效的预测和分析。更多还原

【Abstract】 A supervised artificial neural network to model the nonlinear relationship between parameters of aging temperature and time with respect to properties was proposed for solution Cu-Ni-Si-Cr alloy. The improved model was developed by the Levenberg-Marquardt training algorithm. The results show that the BP neural network was an effective way and can be successfully used to predict and analyze the properties of Cu-Ni-Si-Cr alloy.更多还原