中文摘要：

为了克服传统粗糙集属性约简方法求解效率不高,且难以搜索出满足用户需求的最优属性约简集的问题,提出了一种属性序约简优化算法。该算法基于决策表的完全属性-值空间树结构,在属性约简空间自适应构造小生境超球面邻域半径,并进行约简树的生成、剪枝、约简及动态优化等,快速找到满足用户需求的最优属性序约简集。相关仿真实验表明该算法在保证收敛速度的同时具有较强的属性约简优化性能,是一种能满足用户需求的高效属性序约简算法。

英文摘要：

In order to overcome the poor efficiency of traditional attribute reduction algorithms and the difficulty in searching the optimization attribute reduct set for the user-oriented,a novel attribute order reduct algorithm is proposed here.Based on the attribute-value space tree structure in the decision table,the algorithm can construct the adaptive niche neighborhood radius in the super-sphere,and an attribute reduct tree is constructed,pruned,reduced and optimized.So the global optimization attribute order reduct for the user-oriented is obtained quickly.Experimental results demonstrate the proposed algorithm is better in both convergence efficiency and attribute reduct.So it is efficient to the minimal attribute order reduct for the user-oriented.