A Knowledge Innovation Algorithm Based on Granularity

The structure of Human k nowledge is regarded as granule state by r ough sets theory. Granularity is used to denote this structure of knowledge. Knowledge itself evolves ceaselessly as creatures. Knowledge innovation is an important step of knowledge evolution course. Based on knowledge g ranularity, a knowledge innovation method was proposed in this paper. The main idea of this method is to constitute the partition granularity of knowledge base space ceaselessly depend on the measure consistency of attribute, till the sort of every granules in the granularity is only one. There is only one computation namely the measure consistency of attribute in the algorithm, so the numerical calculation work is little, the time complexity is low, and the algorithm is feasible absolutely. Experiments were taken on the imperfect knowledge base space of day weather classification by this algorithm, its working course wa s explained. The successful results show that this algorithm is correct and valid.