Application of Gray Sequence Prediction in Tax Forecasting

Forecasting the tax gross exactly is significant to carry on the macroscopic regulation efficiently under the market economy .The sample of tax data (1992-1997) in china was analyzed qualitatively .The original data was processed by the introduction of the average-generating arithmetic operators .The GM(1,1) mode was built . Variation rules of the tax data were discovered and mastered .The future data was forecasted quantitatively. In order to make full use of the new information and improve the prediction precision further, the data was processed by metabolism , and the model was built and a second prediction was made .The results show that using the GM(1,1) model to forecast the tax data involves a smaller sample and less information. It’s easier to build the model and the prediction precision is better.