| 基于神经网络的真空感应炉终点钢水温度预报 |
| |
| 引用本文： | 邓长辉,王姝,王福利,桑海峰.基于神经网络的真空感应炉终点钢水温度预报[J].钢铁研究学报,2005,17(4):72-75. |
| |
| 作者姓名： | 邓长辉 王姝 王福利 桑海峰 |
| |
| 作者单位： | 东北大学信息与工程学院,辽宁,沈阳,110004;东北大学信息与工程学院,辽宁,沈阳,110004;东北大学信息与工程学院,辽宁,沈阳,110004;东北大学信息与工程学院,辽宁,沈阳,110004 |
| |
| 基金项目： | 国家重大基础研究规划资助项目(2002CB312200) |
| |
| 摘 要： | 针对真空感应炉生产过程中温度测量成本较高及精度较差等不足，建立了基于RBF神经网络的真空感应炉终点钢水温度预报模型。对输入参数作了详细的分析、筛选，并运用聚类算法对该模型进行了训练。结合现场数据进行了学习和预报，预报命中率较高，表明采用该方法可很好地预报钢水温度。
|
| 关 键 词： | 真空感应炉 神经网络 温度预报 聚类算法 |
| 文章编号： | 1001-0963(2005)04-0072-04 |
End-Point Temperature Prediction Based on Neural Network for Vacuum Induction Melting |
| |
| DENG Chang-hui,WANG Shu,WANG Fu-li,SANG Hai-feng.End-Point Temperature Prediction Based on Neural Network for Vacuum Induction Melting[J].Journal of Iron and Steel Research,2005,17(4):72-75. |
| |
| Authors: | DENG Chang-hui WANG Shu WANG Fu-li SANG Hai-feng |
| |
| Abstract: | A prediction model of molten steel temperature based on RBF neural network was developed to reduce cost and improve temperature control accuracy for vacuum induction melting. The input parameters are described. The network is trained by clustering algorithm. 120 sets of data were used for model building and validation. The experimental results show that the proposed model is effective with high accuracy. |
| |
| Keywords: | vacuum induction furnace neural network temperature prediction clustering algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
