摘要
提出利用神经网络进行切削参数优化的方法,给出了具体的网络实现过程,应用相关性剪枝算法克服了传统方法中网络隐层难以确定的问题。仿真结果表明了该方法的有效性,对高速加工切削参数的选择和切削过程控制具有指导意义。
The optimizing method for turning parameters was put forward based on neural networks, the realizing process of networks was given and correlation pruning algorithm was applied to resolve the problem that the hidden layer nodes of neural networks are hard to determine, the simulation shows the method is effective and can provide a guidance to optimize turning parameters and turning process control.
出处
《工具技术》
2010年第1期43-45,共3页
Tool Engineering
基金
河南省教育厅自然科学研究资助项目(2008A510014)
关键词
神经网络
预测模型
剪枝算法
切削参数
neural network
prediction model
priming algorithm
turning parameter
