A Nearest Neighbor-Radial Basis Function Network to Forecasting Grain Production

摘要：

It is difficult to forecast complex nonlinear time series accurately by traditional prediction methods. A novel time series forecasting method named nearest neighbor-radial basis function networks (NN-RBFN) was designed in this paper through integrating nearest neighbor method with radial basis function networks. The algorithm of NN-RBFN is simple and easy to program, and it can be applied universally. NN-RBFN was applied to forecast our countrys grain production, and satisfying results were obtained. The forecasting results are helpful to government decision-making.

关键词： Time Series Forecasting Nearest Neighbor Method Radial Basis Function Networks Grain Production

作者: Zheng Qifu Su Guodong

作者单位: West Branch of Zhejiang University of Technology, Quzhou, P.R.China, 324000

会议类型: 国际会议

会议名称: 2008年国际应用统计学术研讨会(2008 International Institute of Applied Statistics Studies)

会议地点: 烟台

会议语种:英文

页码: 1-5

在线出版日期: 2008-08-14（万方平台首次上网日期，不代表论文的发表时间）