| 基于多目标进化的属性约简算法 |
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| 引用本文： | 范会联,仲元昌.基于多目标进化的属性约简算法[J].计算机工程,2012,38(8):153-155. |
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| 作者姓名： | 范会联 仲元昌 |
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| 作者单位： | 1. 长江师范学院数学与计算机学院,重庆,408100
2. 重庆大学通信工程学院,重庆,400044 |
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| 基金项目： | 科技部创新基金资助项目(10C26215115008);重庆市教委自然科学基金资助项目(KJ111306) |
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| 摘 要： | 针对粗糙集属性约简问题，提出一种以最小属性子集和最大依赖度为目标的多目标粒子群优化算法。该算法以非支配排序策略为基础，利用加权法寻找最优粒子，使粒子群在新的运动方程和ε-邻域变化策略的混合作用下进化，从而具有更好的全局开拓和局部收搜索能力。在UCI标准数据集上的对比测试结果表明，该算法具有较好的收敛性。
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| 关 键 词： | 粗糙集 非支配排序 属性约简 多目标进化 适应度 |
| 收稿时间： | 2011-08-12 |
Attribute Reduction Algorithm Based on Multi-objective Evolution |
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| FAN Hui-lian
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ZHONG Yuan-chang.Attribute Reduction Algorithm Based on Multi-objective Evolution[J].Computer Engineering,2012,38(8):153-155. |
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| Authors: | FAN Hui-lian ZHONG Yuan-chang |
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| Affiliation: | 1.College of Mathematics and Computer,Yangtze Normal University,Chongqing 408100,China;2.College of Communication Engineering,Chongqing University,Chongqing 400044,China) |
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| Abstract: | Aiming at the problem of attribute reduction,this paper proposes a new multi-objective particle swarm optimization algorithm which aims at the least reduction of attributes sets and maximum of the dependency of the attributes.It searches best particle based on non-dominated sorting and weighting method.Combining the new motion equation with ε-neighborhood perturbation,the algorithm has strong global and local searching ability.Experimental results with UCI data sets show that the proposed algorithm is more effective than the compared algorithms. |
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| Keywords: | rough set non-dominated sorting attribute reduction multi-objective evolution fitness |
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