不协调优势目标信息系统的启发式约简算法

Heuristic algorithm for attribute reduction in inconsistent information systems based on dominance relation

针对不协调优势目标信息系统,引入知识粒度的概念,证明了知识粒度是随着知识的不确定程度的增加而减小的。其次定义了优势信息系统中的粗糙度、精度以及不协调目标信息系统中的近似精度等概念,得到了它们的相关性质,并证明了精度和近似精度可以作为属性重要性的衡量指标。因而进一步提出一种以近似精度为启发信息的不协调优势目标信息系统的启发式约简算法,并分析了该算法的时间复杂度。最后通过实例分析验证了算法的实用性和有效性。

A concept of knowledge granularity in rough sets based on dominance relation is introduced, and conclusion is demonstrated that knowledge granularity declines as the enhancement of uncertain extent of knowledge.On this basis,roughness and accuracy are defined in the information systems based on dominance relation,approximate accuracy in inconsistent objective information systems based on dominance relation.Conclusion is proved that accuracy and approximate accuracy can measure the approximate property of the importance.Furthermore a heuristic reduction algorithm with approximate accuracy is hettristic information raised inconsistent objective information systems based on dominance relation,and the time complexity of the algorithm is analysed as follows.Finally,an example illustrates this algorithm is practical and effective.