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基于改进遗传算法的连续属性离散化方法
引用本文:夏战国,夏士雄,牛强,张磊.基于改进遗传算法的连续属性离散化方法[J].计算机工程与设计,2008,29(16).
作者姓名:夏战国  夏士雄  牛强  张磊
作者单位:中国矿业大学计算机科学与技术学院,江苏,徐州,221116
基金项目:国家自然科学基金,江苏省社会发展基金,教育部高等学校博士学科点专项科研基金,中国矿业大学校科研和教改项目
摘    要:粗糙集中的离散化要求在保持原有决策系统的不可分辩关系情况下,用尽量少的断点进行离散化,而求取连续属性值的最优断点集合是一个NP难题.把连续属性值离散化问题作为一种约束优化问题,采用一种改进的遗传算法来获得最优解,并针对离散化问题设计了相应的编码方式和交叉方法.实验结果表明,采用改进的遗传算法求解连续属性值最优断点集合是可行的.

关 键 词:离散化  决策表  粗糙集  遗传算法  连续属性值

Method of discretization of continuous attributes based on improved genetic algorithm
XIA Zhan-guo,XIA Shi-xiong,NIU Qiang,ZHANG Lei.Method of discretization of continuous attributes based on improved genetic algorithm[J].Computer Engineering and Design,2008,29(16).
Authors:XIA Zhan-guo  XIA Shi-xiong  NIU Qiang  ZHANG Lei
Affiliation:XIA Zhan-guo,XIA Shi-xiong,NIU Qiang,ZHANG Lei(School of Computer Science , Technology,China University of Mining , Technology,Xuzhou 221116,China)
Abstract:The discretization in the rough set requires that it should be maintained indiscernibility of the original decision-making system,use possible minimum number of breakpoints to discrete,and acquiring an optimal breakpoint set of continuous attributes value is a NP problem.The discretization problem of continuous attribute value as a constrained optimization problem,adopted an improved genetic algorithm to obtain the optimal solution,and designed the corresponding coding and cross method for the issue of disc...
Keywords:discretization  decision table  rough set  genetic algorithm  continuous attributes value  
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