Rough set knowledge reduction approach based on improving genetic algorithm

In this paper, a kind of rough set knowledge reduction algorithm based on improving genetic algorithm is proposed by analyzing rough sets reduction. Support degree and importance degree of condition attribute on decision attribute in information system are as heuristic information in Genetic Algorithm. On the basic of that, the GA was improved by population and individual dissimilarity degree in order to enhanced system global optimization and accelerate the convergence rate. The Practical results show that the approach is time-saving and effective for solving knowledge reduction.