基于差分演化算法的粗糙集属性约简

属性约简是粗糙集(RS)理论的核心内容之一。应用差分演化(DE)算法求解最小属性约简是一个新的方向。对差分演化算法进行了改进，给出了一种新的适应值函数的定义形式；并在此基础上提出了基于差分演化算法的属性约简算法。最后利用多组数据对该算法进行了仿真实验，并与现有算法进行了比较分析。实验结果表明该算法是有效的,能快速地进行属性约简。

Attribute reduction of rough set based on differential evolutionary algorithm

The attribute reduction is one of the cores of Rough Set (RS) theory. To solve minimum attribute reduction by Differential Evolution (DE) algorithm is a new direction. In this paper, an improved differential evolution algorithm and a new definition form of fitness function were proposed. And on this basis, an attribute reduction algorithm based on the improved differential evolutionary algorithm was put forward. Finally, the simulation experiments and a comparative analysis with an existing algorithm were carried out for the algorithm with multiple sets of data. The experimental results show that the algorithm is effective and fast.