首页 | 本学科首页   官方微博 | 高级检索  
     

基于神经网络的提拉法钛单晶生长过程建模
引用本文:王岩,雷小博. 基于神经网络的提拉法钛单晶生长过程建模[J]. 钛工业进展, 2006, 23(1): 21-23
作者姓名:王岩  雷小博
作者单位:1. 西安理工大学自动化与信息工程学院,陕西,西安,710048
2. 西安理工大学晶体生长设备研究所,陕西,西安,710048
摘    要:用神经网络建立提拉法钛单晶生长过程的经验模型,并通过试验验证模型的有效性。改进钛单晶生长试验设备,采集建立经验模型所需的无噪实验数据。建立前馈神经网络预测器,建模提拉法钛晶体生长过程非线性动态特性,用自适应BP算法训练神经网络,以加快网络的学习和收敛。

关 键 词:生长模型  提拉法  神经网络  
收稿时间:2005-05-20
修稿时间:2005-05-20

Modeling of Czochralski Single Crystal Growth Process Using Neural Network
Wang Yan,Lei Xiaobo. Modeling of Czochralski Single Crystal Growth Process Using Neural Network[J]. , 2006, 23(1): 21-23
Authors:Wang Yan  Lei Xiaobo
Abstract:First known attempt to empirically modeling and experimentally verifying the growth of ilmenite single crystals using Czockralski process is presented. Czochralski is an industrial crystal pulling process extensively used for silicon and germanium single crystal growth. The experimental apparatus for ilmenite growth process has been significantly improved, and applied to acquisition of noise-free experimental data for empirical modeling. A feedforward multilayer perceptron is used to develop a single-step predictor, modeling the thermal response of the Czochralski single crystal growth process of ilmenite. The training of the neural network is performed using adaptive back-propagation, an accelerated learning algorithm.
Keywords:growth models   Czochralski   neural network   ilmenite
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《钛工业进展》浏览原始摘要信息
点击此处可从《钛工业进展》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号