运用神经网络技术实现材料性能参数的实时识别是智能化拉深的重要研究课题。
The real-time identification via neural network is an important subject in intellectual deep drawing of sheet metal.
提出了一种神经网络参数的初始化方法——向量单位化方法。
The paper puts out a worthy popularized method of Parameter Initialization for neural network-vector unitization method.
轧机自动化以神经网络模型为基础进行道次表、弯辊和窜辊设定点、以及平直度动态控制参数的计算。
Mill automation is based on models with neural networks for pass schedule calculation and computation of set points for roll shifting and bending, and parameters for dynamic flatness control.
在比较两种不同的控制策略模型时发现，神经网络模型适用于控制指令实时输出的参考，而参数化模型更易于在微型直升机的控制系统中使用。
The neural network model was used as the reference output of the control command, while the parameterization model was used in the onboard control system.
作者通过对柴油机性能参数的影响因素的分析，建立柴油机稳态性能预测的人工神经网络模型，并编写可视化程序。
Analyzing the influence factors of the performance of diesel engine, the author created a ANN model for predicting the steady state performance of diesel engine and wrote visual program.
作者通过对柴油机性能参数的影响因素的分析，建立柴油机稳态性能预测的人工神经网络模型，并编写可视化程序。
Analyzing the influence factors of the performance of diesel engine, the author created a ANN model for predicting the steady state performance of diesel engine and wrote visual program.
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