| 基于神经网络的中厚板凸度预报 |
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| 引用本文： | 王冬菊,姚晓兰.基于神经网络的中厚板凸度预报[J].有色金属,2007,59(2):41-42,49. |
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| 作者姓名： | 王冬菊 姚晓兰 |
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| 作者单位： | 1. 安徽师范大学,电子系,安徽芜湖,241000
2. 北京理工大学,信息科学技术学院,北京,100081 |
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| 摘 要： | 应用改进BP神经网络建立中厚板凸度预报的三层神经网络预报模型，用自适应学习速率法和附加动量法两种改进BP算法结合起来训练神经网络模型。试验仿真结果表明，该模型对测试数据预报结果均在3％之内，精度高，训练速度较快，具有很好的实用性。
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| 关 键 词： | 金属材料 中厚板凸度预报 BP改进算法 神经网络 |
| 文章编号： | 1001-0211（2007）02-0041-03 |
| 收稿时间： | 2005-12-29 |
| 修稿时间： | 2005-12-29 |
Crown Prediction of Media and Heavy Plate Based on Neural Network |
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| WANG Dong-ju,YAO Xiao-lan.Crown Prediction of Media and Heavy Plate Based on Neural Network[J].Nonferrous Metals,2007,59(2):41-42,49. |
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| Authors: | WANG Dong-ju YAO Xiao-lan |
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| Affiliation: | 1. Electronic Department, Anhui Normal University, Wuhu 241000 ,Anhui, China ; 2. School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | A three-layered neural network predictive model for crown prediction of media and heavy plate is established by improved neural network. The model is trained with BP algorithm modified with adaptive learn-rate algorithm and additional momentum algorithm. It is indicated by the simulation results that the predictive model is of good utility with high precision and train-speed, the error of the predictive results for the test data is all within 3%. |
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| Keywords: | metal material crown prediction of media and heavy plate improved BP method neural network |
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