An Investigation of Interpolation Scheme Based on Indirect Radial Basis Neural Networks

摘要：

　　An indirect radial basis neural network (IRBNN) is proposed for improving the accuracy of the approximated functions.The IRBNN is constructed by new prompted functions generated from the Nth order derivative of the approximated function.In this way, high accuracy derivatives in different order can be obtained, so that more accuracy of the numerical results would be given while the IRBNN is employed for creating approximated functions in numerical methods.Numerical results through applications in elasticity show the effectiveness and accuracy of the IRBNN method.

关键词： Numerical Method Interpolation Scheme Indirect Radial Basis Neural Networks

作者: Haitao Sun

作者单位: School of Landscape and Architecture,Zhejiang A&F University,311300,Lian,Hangzhou,China

会议类型: 国际会议

会议名称: the 2012 International Conference on Vibration, Structural Engineering and Measurement (2012年振动、结构工程与测量国际会议(ICVSEM2012))

会议地点: 上海

会议语种:英文

页码: 2181-2188

在线出版日期: 2012-10-19（万方平台首次上网日期，不代表论文的发表时间）