Genetic Algorithm Based Multi-Knowledge Extraction Method for Rough Set

Rough theory provides an effective approach for knowledge reduces. A genetic algorithm based multi-knowledge extraction method is proposed for rough set. Multi-reducts algorithm is constructed and multi-knowledge created according to much knowledge reducts in decision system. Based on the above result, the multi-knowledge is optimized by genetic algorithm from a more high level, and the optimized knowledge is extracted. Comparing with single body knowledge, experimental analysis and results show that the multi-knowledge optimized and extracted enhance the precision and can make the knowledge representation more generalizable.