Spatial Combination Forecasting Model and Its Empirical Study
to improve the forecasting accuracy of spatial panel data with the spatial autocorrelation, the significance of spatial autocorrelation by Moran coefficient is tested by Z-statistic. The panel data is considered as a set of time-series data, and the genetic algorithm back-propagation (GABP) neural network forecasting model is established. And the panel data is considered as a set of cross-sectional data, Kriging algorithm forecasting model is established. Then the combination forecasting model of panel data is established by the results of two models, and weighted by the new approach of information entropy. An empirical study is carried out with some counties’ lever of township in Fujian 2007, China. The result shows that the combination forecasting model of spatial panel data based on information entropy is the most effective one.
spatial panel data spatial combination forecasting model information entropy
GAN Jiansheng PAN Yan
School of Management, Fuzhou University, Fuzhou, P.R.China, 350002 Fujian Institute of Economics and School of Management, Fuzhou University, Fuzhou, P.R.China, 350002
国际会议
2009 International Institute of Applied Statistics Studies(2009 国际应用统计学术研讨会)
青岛
英文
1-5
2009-07-25（万方平台首次上网日期，不代表论文的发表时间）