一种基于改进遗传算法的粗糙集属性约简算法

An Attribute Reduction Algorithm for Rough Set Based on Improving Genetic Algorithm

为解决传统遗传算法在属性约简时会出现迭代次数多,收敛较慢的问题,论文提出了一种改进的遗传算法。该方法在适应函数上加入属性重要度因子,同时在交叉操作中有选择地保留子代个体,确保算法能够快速收敛。实验结果证明,改进之后的算法在保证属性约简的基础上,能够实现比传统遗传算法更快的迭代和收敛。

In order to solve the question of more iterative times and the slower convergence speed of traditional genetic algorithm in attribute reduction ,an improved genetic algorithm is proposed .This algorithm gives sufficiency function added a factor of attribute importance ,and saves the individual which have good adaptation in crossover operation ,to make sure the algorithm can quickly converge .The result shows that this method not only ensures attribution reduction ,but also achieves fast iterative and fast convergence .