|
|||||
|
|
| 基于RBF神经网络的热连轧精轧厚度的预报 | |
| 引用本文： | 刘东东,王焱. 基于RBF神经网络的热连轧精轧厚度的预报[J]. 济南大学学报(自然科学版), 2006, 20(4): 312-314 |
| 作者姓名： | 刘东东 王焱 |
| 作者单位： | 济南大学,控制科学与工程学院,山东,济南,250022;济南大学,控制科学与工程学院,山东,济南,250022 |
| 摘 要： | 采用RBF神经网络方法建立热连轧精轧的厚度模型，通过比较有、无理论模型输入的神经网络厚度模型确定出理论数据在神经网络应用中的重要性。通过比较BP神经网络和RBF神经网络分别建立的厚度模型凸现出RBF神经网络厚度模型的优越性，并在应用过程中解决了过拟合问题。 |
| 关 键 词： | 人工神经网络 RBF算法 热连轧 厚度预报 |
| 文章编号： | 1671-3559(2006)04-0312-03 |
| 修稿时间： | 2006-03-01 |
Prediction of Rolling Thickness Based on RBF Neural Network |
|
| LIU Dong-dong,WANG Yan. Prediction of Rolling Thickness Based on RBF Neural Network[J]. Journal of Jinan University(Science & Technology), 2006, 20(4): 312-314 | |
| Authors: | LIU Dong-dong WANG Yan |
| Abstract: | A rolling thickness model is established using RBF neural networks.Compared with the thickness models that have or have not traditional models as input,the importance of traditional models in the application of neural networks is obvious.Rolling thickness models are established to improve the prediction precision of rolling thickness using BP and RBF neural networks.The result of two models indicates that RBF neural networks are more accurate,and the over-fitness problems in actual application have been solved also. |
| Keywords: | artificial neural networks RBF algorithm hot strip mills prediction of rolling thickness |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |