Caveman网络及其在复杂网络熵分析中的应用
发布时间：2018-10-20 14:47
【摘要】：熵可以有效反映复杂系统内网络结构的异质性.针对熵指标在刻画网络全局异构上是否适用这一问题,目前仍缺少用以评测的基准网络.对此,在已有结构熵研究的基础上,提出一种Caveman网络构造及其演化规则,为网络复杂性的度量提供新的思路。通过数理分析和仿真实验验证该Caveman网络可以有效评测各类结构熵指标对其演化过程的敏感性,反映熵指标对网络复杂特征识别能力的差异。同时由于Caveman网络可以更好地探索信息空间和抵御攻击,将有助于设计鲁棒、高效的系统结构。
[Abstract]:Entropy can effectively reflect the heterogeneity of network structure in complex systems. In order to solve the problem of whether entropy index is applicable to describe the global heterogeneity of network, there is still a lack of benchmark network for evaluation. In this paper, based on the study of the existing structure entropy, a new method of Caveman network construction and its evolution rules is proposed, which provides a new idea for the measurement of network complexity. Through mathematical analysis and simulation experiments, it is proved that the Caveman network can effectively evaluate the sensitivity of various structural entropy indexes to its evolution process, and reflect the difference in the ability of entropy index to recognize complex features of the network. At the same time, because Caveman network can better explore information space and resist attacks, it will be helpful to design a robust and efficient system structure.
【作者单位】： 西安电子科技大学经济与管理学院;西安交通大学公共管理与复杂性科学研究中心;斯坦福大学莫里森人口与资源研究所;
【基金】：国家自然科学基金(71501153) 国家社会科学基金重点项目(12AZD110) 陕西省软科学研究计划(2015KRM051) 中央高校基本科研业务费专项资金(JB150602)~~
【分类号】：O157.5
，
本文编号：2283477
[Abstract]:Entropy can effectively reflect the heterogeneity of network structure in complex systems. In order to solve the problem of whether entropy index is applicable to describe the global heterogeneity of network, there is still a lack of benchmark network for evaluation. In this paper, based on the study of the existing structure entropy, a new method of Caveman network construction and its evolution rules is proposed, which provides a new idea for the measurement of network complexity. Through mathematical analysis and simulation experiments, it is proved that the Caveman network can effectively evaluate the sensitivity of various structural entropy indexes to its evolution process, and reflect the difference in the ability of entropy index to recognize complex features of the network. At the same time, because Caveman network can better explore information space and resist attacks, it will be helpful to design a robust and efficient system structure.
【作者单位】： 西安电子科技大学经济与管理学院;西安交通大学公共管理与复杂性科学研究中心;斯坦福大学莫里森人口与资源研究所;
【基金】：国家自然科学基金(71501153) 国家社会科学基金重点项目(12AZD110) 陕西省软科学研究计划(2015KRM051) 中央高校基本科研业务费专项资金(JB150602)~~
【分类号】：O157.5
，
本文编号：2283477
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