Prediction of Cutting Consumption based on Optimization-Making RBF Artificial Neural Network

摘要：

　　Excision rate was fitted and predicted via building on cutting parameters affecting cutting machining process with Optimization-Making RBF (OMRBF) Neural Network.Radial basis function was made to select the best optimized distribution density in order to advance the fitting and forecasting capability of RBF.The result of OMRBF was compared with BP Neural Networks,what showed that the fitting and forecasting accuracy of OMRBF was much higher than BP Neural Networks.

关键词： Optimization-Making RBF BP Neural Network cutting parameter Optimization-Making

作者: Minqing Gong Mingwei Sun Min Huang Shuwen Xiang

作者单位: Science College, Guizhou University, Guiyang, Guizhou, 550025 PR China

会议类型: 国际会议

会议名称: the 2012 International Conference on Frontiers of Advanced Materials and Engineering Technology (2012年先进材料与工程技术国际会议(FAMET 2012))

会议地点: 厦门

会议语种:英文

页码: 659-663

在线出版日期: 2012-01-04（万方平台首次上网日期，不代表论文的发表时间）