• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Joint International Information Technology and Artificial Intelligence Conference >The prediction algorithm of network security situation based on grey correlation entropy Kalman filtering
【24h】

The prediction algorithm of network security situation based on grey correlation entropy Kalman filtering

机译：基于灰色相关熵Kalman滤波的网络安全情况预测算法

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

摘要

Based on the review of current prediction algorithms of network security situation, prediction algorithms based on Kaiman filtering are studied. A prediction algorithm of network security situation based on grey correlation entropy Kaiman filtering is presented, hoping to be more helpful to network administrators through providing them information more effectively. First correlation of factors influencing network security situation is analyzed by Grey correlation entropy analysis method, and key influencing factors are selected. Then according to these influencing factors corresponding process equation and prediction equation are established. Finally, network security situation prediction is made recursively by Kaiman filtering. Experiment results show that the prediction by this method is more precise compared to GM(1, 1) and general Kaiman algorithm, and its real-time performance is better than RBF algorithm.
机译：基于对网络安全情况的当前预测算法的审查，研究了基于Kaiman滤波的预测算法。 提出了一种基于灰色相关熵的网络安全情况的预测算法，希望通过更有效地向网络管理员提供更多帮助网络管理员。 通过灰色相关熵分析方法分析了影响网络安全情况的因素的第一个相关性，选择了关键的影响因素。 然后根据这些影响因素，建立了相应的处理方程和预测方程。 最后，通过kaiman滤波递归地进行网络安全情况预测。 实验结果表明，与GM（1,1）和一般凯门算法相比，该方法的预测更精确，其实时性能优于RBF算法。

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