bp artificial neural network and genetic algorithm were applied to the parameters optimization of profile extrusion die on base of the matlab foundation.
基于matlab平台,将bp人工神经网络与遗传算法应用于型材挤压模具参数优化设计。
bp artificial neural network, genetic algorithm and finite element method(fem) simulation were applied to optimization of the deflector hole design of profile extrusion die on matlab foundation.
基于matlab平台,将bp人工神经网络、遗传算法和数值模拟技术应用于铝型材挤压模具的导流孔形状优化设计。
the effect of major parameters of die structure on metal flow velocity is integrated and the mathematical model of design and calculation of aluminum profile extrusion die land length is derived.
并综合主要模具结构参数对金属流动速度的影响,建立了铝型材挤压模模孔工作带设计计算的数学模型。
bp artificial neural network, genetic algorithm and fem simulation were applied to optimize the design of profile extrusion die on matlab foundation.
基于matlab平台,将bp神经网络、遗传算法和数值模拟技术应用于铝型材挤压模具参数优化设计。