Abstract: Based on the combination of variable precision approximations and grade approximations,as well as the core position of positive region, rough set model of variable precision upper approximation and grade lower approximation was constructed, and positive region in the model was defined. Related to precision and grade quantitative indexes, the connotation and significance of the positive region were investigated, and precise description and some properties were obtained. In order to calculate the positive region, natural and atomic algorithms were proposed and analyzed, and a conelusion was drawn that natural and atomic algorithms have the same time complexity while atomic algorithm has more advantages in space complexity. Finally, a medical example was given to analyze and explain the positive region and the algorithms. Positive region in rough set model of variable precision upper approximation and grade lower approximation has completely expanded positive region in classical rough set model in a perfect direction, and has great values to necessity knowledge discovery related to precision and grade parameters.

Key words: Artificial intelligence, Rough set theory, Rough set model, Variable precision approxi-mation, Graded approximation, Positive region