模糊软集合理论在税收组合预测中的应用

结合模糊软集合理论建立税收收入的组合预测模型,根据税收收入的特点,代表性地选择了Elman回归神经网络模型、含政策虚拟变量的自回归模型、ARIMA(1,1,1)的时间序列模型、多因素SVM回归模型这四种模型作为组合预测中的单一模型,并以1980年到2008年的税收收入等相关数据为背景进行了说明和分析.结果表明该组合预测模型能有效减小预测误差,为税收工作实践提供了一个应用研究工具,并推广和丰富了软集合理论在税收经济模型研制中的实际应用.

Application of fuzzy soft sets in tax combined forecasting

Fuzzy soft set theory to establish a combination of tax revenue forecasting model,based on the characteristics of tax revenue,representative selection of the Elman recurrent neural network model,with the policy dummy variables from the regression model,ARIMA(1,1,1)time series models,multi-factor regression model of these four SVM model as a combination of a single model for forecasting.Also,this paper described and analyzed the selected tax revenue and other relevant data of our country from 1980 to 2008.Th...