首页> 外文会议>International Conference on Education, Management, Information and Mechanical Engineering >Design of Association Rules Data Mining System Based on Improved Ant Colony Algorithm
【24h】

Design of Association Rules Data Mining System Based on Improved Ant Colony Algorithm

机译:基于改进蚁群算法的关联规则数据挖掘系统设计

获取原文

摘要

Data Mining is from large, incomplete, noisy, fuzzy and random Data, extract implicit in it, people don't know in advance, but it is potentially useful information and knowledge of the process. The Ant Colony algorithm is actually positive feedback principle, and it is an algorithm combining the heuristic algorithm. The Ant Colony algorithm is easy to fall into local optimum and slow convergence, many new models are put forward, such as ACA based on cloud model. The paper presents design of association rules data mining system Based on improved ant colony algorithm.
机译:数据挖掘来自大,不完整,嘈杂,模糊和随机的数据,提取物隐含,人们提前不知道,但它是潜在的有用信息和过程的知识。 蚁群算法实际上是正反馈原理,并且是一种组合启发式算法的算法。 蚁群算法容易下降到局部最佳和缓慢的收敛中,提出了许多新型号,例如基于云模型的ACA。 本文介绍了基于改进蚁群算法的关联规则数据挖掘系统设计。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号