基于改进启发式遗传算法的属性约简方法  

Modified Heuristic Genetic Algorithm for Reduction of Attributes

作　　者：王锋[1] 侯海平[1] 孙辉[1] 

机构地区：[1]大连交通大学软件学院,辽宁大连116028

出　　处：《计算机与现代化》2008年第10期1-4,共4页Computer and Modernization

基　　金：教育部科学技术研究资助项目(204032)

摘　　要：为了获得决策系统中属性的极小相对约简,将决策表中相对于每个条件属性的集合和划分的粗糙逼近精度作为衡量属性重要程度的准则,并以此作为启发式信息引入遗传算法,提出一种在优化初始种群的基础上提高算法性能的启发式遗传算法。通过构造一个修正算子并将其引入启发式信息,以保证被选择的属性子集的分类能力不变。该算子利用启发式信息的局部搜索技术,使得算法既保持了整体的优化特性,又具有较快的收敛速度。实例证明,该算法能有效地对决策系统进行约简。This paper regards the significance of attributes defined from the approximation quality with respect to the partition and condition attributes set as heuristic information, and proposes the heuristic information into genetic algorithm based on optimizing initial population. A new modify operator is used for introducing the heuristic information so as to maintain the ability of classification of the attributes set. The operator is an embodiment of local research method using heuristic information. So the algorithm converges quickly and has global optimizing ability. The algorithm is also analyzed theoretically and the correctness and effectiveness of the algorithm are shown in the experiments.

关 键 词：粗糙集 逼近精度 属性约简 遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]