为使粗糙集理论能有效处理含噪音的不完备信息系统,将集对势扩充粗糙集模型和Ziarko教授提出的多数包含关系相结合,提出了变精度集对势粗糙集模型.然后,给出了正域相似度的定义,提出了基于正域相似度的启发式属性约简算法,并分析了算法的时间复杂度.仿真实验表明了该方法处理含噪音的不完备信息系统的有效性. In order to make the rough set theory effectively deal with the incomplete information system with noises, we propose a rough set model of variable precision co-ordination by combining the contradictory augmented rough set model with the most inclusive one proposed by Professor Ziarko. Then, The definition of the similarity of the positive domain is proposed, and the heuristic attribute reduction algorithm based on the similarity of the positive domain is proposed, and the time complexity of the algorithm is analyzed. The simulation results show that this method is effective in dealing with the incomplete information system with noises.