Application Research on Tax Forecasting in China Based on Rough Set Theory
粗糙集理论在我国税收预测中的应用

According to rough set theory,this paper puts forward a conception of the degree of credibility between objects and rules, and attempts to present a related relation prediction method. Information entropy is employed to reduce factors, assess the importance of them and derive basic related rules. On the basis of the degree of credibility,a prediction model is presented. Compared with traditional regression prediction, this approach does not need to proceed relativity judgment, pattern recognition and examination, while it will reduce redundancy factors without losing information directly from data in order to mine the related relation between economic indices and influent factors. This method can deal with qualitative,quantitative and uncertainty factors. The results prove the usefulness of the proposed method for a practical tax forecasting model.