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基于改进粒子群优化的粗糙集连续属性离散化
引用本文:汪凌,胡培.基于改进粒子群优化的粗糙集连续属性离散化[J].计算机工程与应用,2010,46(15):115-117.
作者姓名:汪凌  胡培
作者单位:西南交通大学,经济管理学院,成都,610031
基金项目:江西省教育厅科研项目(No.JC0904,No.GJJ09145)
摘    要:提出一种基于改进粒子群优化的连续属性离散化算法。在算法优化方面,采用改进粒子群优化算法。为了克服传统粒子群优化的不足,对种群初始化和自适应调整粒子的惯性权重,提高了粒子群优化算法的全局寻优能力。在粗糙集属性离散化方面,主要是通过将最小断点集作为优化目标,粗糙集属性依赖度作为约束条件。仿真结果表明,该方法能有效地解决决策表连续属性离散化问题,计算速度快,收敛性好。

关 键 词:改进粒子群优化  粗糙集  连续属性离散化
收稿时间:2010-1-25
修稿时间:2010-3-15  

Discretization algorithm of rough set continuous attributes based on improved Particle Swarm Optimization
WANG Ling,HU Pei.Discretization algorithm of rough set continuous attributes based on improved Particle Swarm Optimization[J].Computer Engineering and Applications,2010,46(15):115-117.
Authors:WANG Ling  HU Pei
Affiliation:School of Economics & Management,Southwest Jiaotong University,Chengdu 610031,China
Abstract:A discretization algorithm of rough set continuous attribute based on improved particle swarm optimization is proposed. For optimization of algorithm,Improved particle swarm optimizaiton is utilized.In order to overcome some defects with PSO,Initialization of the population and the inertia weight are adjusted,the diversity ability of particle swarm optimization is improved.For rough set attribute discretization,it is mainly through minimum break point sets as optimization goals and rough set attribute depen...
Keywords:improved particle swarm optimization  rough sets  continuous attribute discretization
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