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用神经网络BP算法预测钨合金材料抗拉强度
Prediction of tungsten tensile strength with artificial BP neural network method
【摘要】 为减少实验量,降低实验成本,采用人工神经网络BP算法处理了钨合金材料的抗拉强度的实验数据,包括钨含量、变形量对材料抗拉强度的影响,给出了在不同钨含量条件下变形量对材料抗拉强度的关系曲线,和不同变形量条件下钨含量对材料抗拉强度的关系曲线.通过本文的分析可知,采用BP算法来处理钨合金的实验数据是可行的.
【Abstract】 In this paper,the tension experimental data of tungsten alloy were processed by BP Neural Network method,including the influences of the W content and deformation magnitude on the tensile strength.Thus two relation curves were drawn,which illustrated the relation between deformation magnitude and material tensile strength when W contents were changed,and the relation between W contents and material tensile strength in the case of different deformation magnitude.It is shown that BP Neural Network may be used to predict the trend of tensile strength of WHA with the changes of shapes and volume fractions of w-phase.
【Key words】 artificial neural network; BP method; tensile strength; deformation magnitude; volume fractions of w-phase;
- 【文献出处】 材料科学与工艺 ,Materials Science and Technology , 编辑部邮箱 ,2006年01期
- 【分类号】TG115.5
- 【被引频次】10
- 【下载频次】238