| 一种基于蚁群算法的分类规则挖掘算法 |
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| 引用本文： | 常晓磊,闫仁武.一种基于蚁群算法的分类规则挖掘算法[J].计算机技术与发展,2007,17(7):114-116. |
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| 作者姓名： | 常晓磊 闫仁武 |
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| 作者单位： | 江苏科技大学,电子信息学院,江苏,镇江,212003 |
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| 摘 要： | Parepinelli等提出了基于ACO的分类算法。文中提出了一种基于自适应蚁群算法的分类规则挖掘算法，该算法采用了与Parepinelli算法不同的启发式函数及信息素改变方法．引入了自适应机制与变异策略，从而达到缩短蚁群算法计算时间、加快算法收敛速度、提高预测准确率的目的。实验结果验证了该算法的有效性。
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| 关 键 词： | 蚁群算法 分类规则 自适应机制 变异策略 |
| 文章编号： | 1673-629X（2007）07-0114-03 |
| 收稿时间： | 2006-10-25 |
| 修稿时间： | 2006-10-25 |
An Improved Classification Rule Mining Based on Ant Colony Algorithm |
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| CHANG Xiao-lei,YAN Ren-wu.An Improved Classification Rule Mining Based on Ant Colony Algorithm[J].Computer Technology and Development,2007,17(7):114-116. |
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| Authors: | CHANG Xiao-lei YAN Ren-wu |
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| Affiliation: | College of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
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| Abstract: | Parepinelli proposed ACO classification algorithm. The paper proposes an improved classification rule mining based on ant colony algorithm. This algorithm uses new heuristic computation and pheromone update methods. Otherwise, an adaptive mechanism and a mutation strategy are applied to the algorithm for the purpose of shortening the computing time and improving the the accurate rate of prediction. The experiment result shows the validity of it. |
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| Keywords: | ant colony algorithm classification rule adaptive mechanism mutation strategy |
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