• 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 >Using Differential Evolution Algorithm and Rough Set Theory to Reduce the Features for Cataract Disease in a Medical Diagnosis System
【24h】

Using Differential Evolution Algorithm and Rough Set Theory to Reduce the Features for Cataract Disease in a Medical Diagnosis System

机译：利用差分进化算法和粗糙集理论减少医学诊断系统中白内障疾病的特征

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

摘要

Rough set theory can deal with vagueness and uncertainty in data analysis, and can efficiently remove redundant information in many areas. There are many features that help to assessment of the diseases, also this data contain irrelevant features, while uncertainties and missing values also exist. In this paper, Differential Evolution (DE) has been used to reduce the features based on the rough set method on the some of the cataracts people. Differential evolution algorithm is a new heuristic approach that having many motivations for using, such finding the true global minimum of a multimodal search space with too many derivations that is very difficult to find, regardless of the initial parameter values, fast convergence rate, and need to tuning a few control parameters. Since the act of choosing the distinguishing features have an unsparing efficiency on the optimized and speedy assessment of diseases, using a convergence and fast algorithm such DE has been suggested.
机译：粗糙集理论可以处理数据分析中的模糊性和不确定性，并且可以有效地去除许多领域中的冗余信息。有许多有助于评估疾病的特征，这些数据也包含不相关的特征，同时还存在不确定性和缺失值。在本文中，基于粗糙集方法，对一些白内障人群使用了差分进化（DE）来简化特征。差分演化算法是一种新的启发式方法，具有多种使用动机，例如，无论初始参数值，快速收敛速度和需求如何，都很难找到具有太多导数的多峰搜索空间的真实全局最小值。调整一些控制参数。由于选择区别特征的行为在疾病的优化和快速评估方面具有不可估量的效率，因此已经提出了使用收敛和快速算法的DE。

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