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以坩埚H/D值、V2O5还原率、V2O5收得率、TiO2还原率和TiO2收得率为输入参数,钒基合金V3TiNi0.56收得率为输出参数,训练过程采用trainlm函数,设计了具有较高精确度的BP神经网络优化模型,可推广应用到各种钒基合金的自蔓延高温合成工艺参数的优化。
Taking the crucible H / D value, the V2O5 reduction rate, the V2O5 yield, the TiO2 reduction rate and the TiO2 yield as the input parameters, the yield of vanadium-based alloy V3TiNi0.56 was taken as the output parameter. The trainlm function was adopted during the training process, The BP neural network optimization model with higher accuracy can be popularized and applied to the optimization of the SHS process parameters of various vanadium-based alloys.