• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>ICCCI 2010;International conference on computer and computational intelligence >A New Feature Selection Method Based on Ant colony and Genetic Algorithm on Persian Font Recognition
【24h】

A New Feature Selection Method Based on Ant colony and Genetic Algorithm on Persian Font Recognition

机译：基于蚁群和遗传算法的波斯字体识别新特征选择方法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Dimensionality reduction of a feature set is a usual pre-processing step used for classification applications to improve their accuracy with a small and appropriate feature subset. In this article, a new hybrid of ant colony optimization (ACO) and genetic algorithm (GAs) as a feature selector, and support vector machine as a classifier are integrated effectively. Based on the combination of the fast global search ability of GA and the positive feedback mechanism of ACO, a novel algorithm was proposed in the domain of feature selection. Experiments show that the proposed feature selection can achieve better performance than that the normal GA and ACO does. We tested this method on the extracted features of ten common Persian fonts. The result shows it has affected slightly better on the performance. Furthermore, number of features decreased to almost half of the original feature number after this pre-processing step.
机译：特征集的降维是用于分类应用程序的常规预处理步骤，以通过较小且适当的特征子集提高其准确性。在本文中，有效地集成了蚁群优化（ACO）和遗传算法（GAs）作为特征选择器和支持向量机作为分类器的新混合体。基于遗传算法的快速全局搜索能力和蚁群算法的正反馈机制，提出了一种新的特征选择算法。实验表明，所提出的特征选择比常规的GA和ACO能够获得更好的性能。我们对十种常见波斯字体的提取特征测试了该方法。结果表明，它对性能的影响略好一些。此外，在此预处理步骤之后，特征数量减少到原始特征数量的几乎一半。

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