【摘要】：熵可以有效反映復雜系統(tǒng)內(nèi)網(wǎng)絡結構的異質性.針對熵指標在刻畫網(wǎng)絡全局異構上是否適用這一問題,目前仍缺少用以評測的基準網(wǎng)絡.對此,在已有結構熵研究的基礎上,提出一種Caveman網(wǎng)絡構造及其演化規(guī)則,為網(wǎng)絡復雜性的度量提供新的思路。通過數(shù)理分析和仿真實驗驗證該Caveman網(wǎng)絡可以有效評測各類結構熵指標對其演化過程的敏感性,反映熵指標對網(wǎng)絡復雜特征識別能力的差異。同時由于Caveman網(wǎng)絡可以更好地探索信息空間和抵御攻擊,將有助于設計魯棒、高效的系統(tǒng)結構。
[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.
【作者單位】： 西安電子科技大學經(jīng)濟與管理學院;西安交通大學公共管理與復雜性科學研究中心;斯坦福大學莫里森人口與資源研究所;
【基金】：國家自然科學基金(71501153) 國家社會科學基金重點項目(12AZD110) 陜西省軟科學研究計劃(2015KRM051) 中央高校基本科研業(yè)務費專項資金(JB150602)~~
【分類號】：O157.5
，

本文編號：2283477