...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Physica Scripta: An International Journal for Experimental and Theoretical Physics >Identifying node importance based on information entropy in complex networks
【24h】

Identifying node importance based on information entropy in complex networks

机译：复杂网络中基于信息熵的节点重要性识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, we firstly put forward a novel correlation centrality index, which considers the node importance contribution in the whole network adequately to overcome the insufficiencies of the interaction between the adjacent nodes. Then, we propose a multi-attribute node importance decision making method based on entropy, which combines the advantages of degree centrality, efficiency centrality, betweenness centrality and correlation centrality, to make up for the one-sidedness of a single index in node importance evaluation. Finally, we demonstrate the accuracy of the correlation centrality index compared with the evaluation matrix method by simulating cascading failures on the Advanced Research Project Agency network; we verify the validity and feasibility of our multi-attribute node importance evaluation method by removing the top six important nodes contrasted to the other methods. We believe that our work will have more practical implications for protecting the key nodes identified in the real world.
机译：在本文中，我们首先提出了一种新的相关性中心度指标，该指标充分考虑了整个网络中节点的重要性贡献，以克服相邻节点之间交互的不足。然后，提出了一种基于熵的多属性节点重要性决策方法，该方法结合了度中心性，效率中心性，中间性中心和相关中心性的优势，弥补了节点重要性评价中单一指标的偏性。 。最后，我们通过模拟高级研究计划局网络上的级联故障，证明了与评估矩阵法相比，相关中心指数的准确性;通过与其他方法相比，我们删除了前六个重要节点，从而验证了我们的多属性节点重要性评估方法的有效性和可行性。我们相信，我们的工作将对保护现实世界中确定的关键节点具有更多实际意义。

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