【摘要】 在试验的基础上 ,采用人工神经网络方法建立了基于BP算法的熔敷金属力学性能的预测模型 ,该模型训练结果与试验值之间有很好的对应关系 ,说明该模型能准确反映合金元素与熔敷金属力学性能之间复杂的非线性关系。用该模型研究了合金元素对熔敷金属低温韧性的影响 ,分析得出了与试验一致的结果更多还原

【Abstract】 A mechanical property prediction model for deposited metals is built upon the experimental data with the aid of artificial neural network (ANN) based on the BP algorithm. There are good correlations between the learining results and the experimental data. It is shown that this model is able to represent the non linear relations between the alloying elements and the mechanical properties of deposited metal accurately. Effect of alloying elements on low temperature toughness was studied by this prediction model, the analyses results were consistent with the experiments.更多还原