| 改进型BP 神经网络对球面磨削最高温度的模拟与预测 |
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| 引用本文： | 蒋天一,胡德金,许开州,许黎明.改进型BP 神经网络对球面磨削最高温度的模拟与预测[J].上海交通大学学报,2011,45(6):901-906. |
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| 作者姓名： | 蒋天一 胡德金 许开州 许黎明 |
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| 作者单位： | (上海交通大学 机械与动力工程学院 , 上海 200030) |
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| 基金项目： | 国家自然科学基金资助项目(51075273); 机械系统与振动国家重点实验室资助项目(MSVMS201104); 华中科技大学数字制造装备与技术国家重点实验室开放课题(2008-DMET-KF-001) |
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| 摘 要： | 基于人工神经网络良好的非线性逼近特性，利用正交试验结果作为神经网络的训练样本，建立基于批训练的改进型误差反向传播(BP)神经网络，并通过Levenberg-Marquardt算法使网络误差最小化，配合Bayesian正则化使网络的误差平方和、网络权重以及阈值平方和实现最优化组合.结果表明，改进型BP神经网络具有较快的收敛速度、较好的泛化性和较强的稳定性，能够准确模拟和预测球面磨削中的最高温度.
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| 关 键 词： | 神经网络 球面磨削 正交试验 磨削温度 Levenberg-Marquardt算法 |
| 收稿时间： | 2010-08-03 |
Simulation and Prediction of the Maximum Temperature in sphere Grinding with Improved BP Neural Network Model |
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| JIANG Tian-yi,HU Den-jin,XU Kai-zhou,XU Li-ming.Simulation and Prediction of the Maximum Temperature in sphere Grinding with Improved BP Neural Network Model[J].Journal of Shanghai Jiaotong University,2011,45(6):901-906. |
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| Authors: | JIANG Tian-yi HU Den-jin XU Kai-zhou XU Li-ming |
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| Institution: | (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200030, China) |
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| Abstract: | Based on the outstanding characteristic of nonlinear convergence of neural network,an improved BP neural network was established.Orthogonal experiments were carried out to provide batch training samples for the network.And the Levenberg-Marquardt algorithm was used to minimize the errors of the network.In addition,the Bayesian regularization was employed to optimize the combination of squared errors,weights and the sum of squared threshold.The experimental results show that the improved BP neural network ha... |
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| Keywords: | neural network sphere grinding rthogonal experiment grinding temperature Levenberg-Marquardt algorithm |
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