中国机械工程2016，Vol.27Issue(20)：2749-2753,2758,6.DOI:10.3969/j.issn.1004-132X.2016.20.010
基于LM-BP神经网络的非线性轮廓图优化方法研究
A Optimization Method for Non-linear Profile Based LM-BP Neural Networks
摘要
Abstract
A method to optimize the non-linear profile was presented based on the DOE theory BP neural network model with Levenberg-Marquard algorithm,which were compared with the traditional statistical regression modeling by a example.The results show that the estimation errors of the model coefficients due to the design and experimental errors may be avoided based on LM-BP neural network modeling.Compared with the BP algorithm this method overcomes the standard BP algorithm per-formance of unstability,slow convergence and low convergence precision,the presence of local mini-ma and other short-comings.The method proposed herein has a high accuracy,optimization results are satisfactory.关键词
BP神经网络/Levenberg-Marquard算法/试验设计/非线性轮廓图Key words
BP neural networks/Levenberg-Marquard (LM)algorithm/design of experiment (DOE)/non-linear profile分类
管理科学引用本文复制引用
许静,何桢,袁荣..基于LM-BP神经网络的非线性轮廓图优化方法研究[J].中国机械工程,2016,27(20):2749-2753,2758,6.基金项目
国家杰出青年科学基金资助项目(71225006) （71225006）
