ON THE MODELING AND APPLICATION OF RBF NEURAL NETWORK

摘要：

At present, the high power DC graphitizing furnace is widely applied, but the temperature-control accuracy is not perfect. In order to improve the temperature-control, we decided first modeling the high power DC graphitizing furnace and then applying the intelligent control. Here we studied the modeling strategy of RBF neural network. Two approaches for the selection of centers of the RBF neural network are discussed.All the simulated results show that the discussed approaches are effective.

关键词： RBF neural network Selection of centers DC graphitizing Furnace Orthogonal Forward Regression, Direct Typical-Point Selection

作者: Liping Qu Jianming Lu Takashi Yahagi

作者单位: Information Engineering school, BeiHua University, Jilin City, Jilin Province 132021,China;Graduate Graduate School of Science and Technology, Chiba University, Chiba City,Chiba 263-8522,Japan

会议类型: 国际会议

会议名称: 2006 International Symposium on Distributed Computing and Applications to Business,Engineering and Science(2006年国际电子、工程及科学领域的分布式计算应用学术研讨会)

会议地点: 杭州

会议语种:英文

页码: 693-695

在线出版日期: 2006-10-12（万方平台首次上网日期，不代表论文的发表时间）