|
|||||
|
|
| 小波RBF神经网络在高炉铁水硅含量预测中的应用 | |
| 引用本文： | 万金镇,秦莉娜,路永辉.小波RBF神经网络在高炉铁水硅含量预测中的应用[J].甘肃冶金,2009,31(2):19-21. |
| 作者姓名： | 万金镇 秦莉娜 路永辉 |
| 作者单位： | 1. 北京市科海龙华工业自动化仪器有限公司,北京,100015 2. 石家庄煤矿机械有限责任公司,河北石家庄,050031 3. 河北理工大学计算机与自动控制学院,河北唐山,063009 |
| 摘 要： | 在运用RBF神经网络进行预测的基础上，建立了一种应用小波理论对时间信号进行去噪，根据去噪处理对RBF神经网络作相应处理的预测模型，并将所建模型应用于预测高炉铁水硅含量。仿真结果表明小波RBF神经网络比RBF神经网络更具优越性，预测准确率明显提高。 |
| 关 键 词： | 小波理论 RBF神经网络 高炉炉温 铁水硅含量 |
The Application of Wavelet RBF Neural Network in Blast Furnace Temperature Forecast |
|
| WAN Jin-zhen,QIN Li-na,LU Yong-hui.The Application of Wavelet RBF Neural Network in Blast Furnace Temperature Forecast[J].Gansu Metallurgy,2009,31(2):19-21. | |
| Authors: | WAN Jin-zhen QIN Li-na LU Yong-hui |
| Affiliation: | 1.Beijing Kehai Longhua Industrial Automation Instrument Ltd.;Beijing 100015;China;2.Shijiazhuang Coal Mining Machinery Co.;Ltd.;Shijiazhuang 050031;3.College of Computer and Automation;Hebei Polytechnic University;Tangshan 063009;China |
| Abstract: | On the basis of RBF neural network,setting up a metal of forecasting silicon content in hot metal based on wavelet RBF neural network,which uses the wavelet theory to denoise the time signal first.The practical results shows that the proposed method has increased significantly the hitting rate of silicon content in hot metal comparing with RBF neural network. |
| Keywords: | wavelet theory RBF neural network the temperature of blast furnace silicon content in hot metal |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |