| 一种基于点和边差异性的网络结构熵 |
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| 引用本文： | 蔡萌,杜海峰,任义科,费尔德曼.一种基于点和边差异性的网络结构熵[J].物理学报,2011,60(11):110513-110513. |
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| 作者姓名： | 蔡萌 杜海峰 任义科 费尔德曼 |
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| 作者单位： | 1. 西安交通大学管理学院, 西安 710049;
2. 西安交通大学公共管理与复杂性科学研究中心, 西安 710049;
3. 山西师范大学管理学院, 临汾 041004;
4. 斯坦福大学莫里森人口与资源研究所,斯坦福 94305 |
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| 基金项目： | 国家教育部新世纪优秀人才支持计划(批准号:NCET-07-0668,NCET-08-0451)、国家自然科学基金(批准号:71071128)、西安交通大学"985工程 "三期、中央高校基本科研业务费专项资金和教育部长江学者和创新团队发展计划(批准号:IRT0855)资助的课题. |
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| 摘 要： | 熵是反映网络异构性的重要指标. 由于只是关注网络结构中"点"或"边"的单一作用,基于度分布和度相对值的两种传统熵在刻画网络结构特征时均存在缺陷. 文章综合考虑"点"和"边"差异性,定义一种新的网络结构熵,并对规则网络、随机网络和无标度网络等结构熵进行理论分析和仿真实验. 结果表明,这种新网络结构熵可以更有效地反映网络的结构特征,尤其是对于稀疏网络及星型网络的结构差异解释更为合理.
关键词：
均匀网络
无标度网络
熵
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| 关 键 词： | 均匀网络 无标度网络 熵 |
| 收稿时间： | 1/5/2011 12:00:00 AM |
A new network structure entropy based node difference and edge difference |
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| Cai Meng,Du Hai-Feng,Ren Yi-Ke and Marcus W.A new network structure entropy based node difference and edge difference[J].Acta Physica Sinica,2011,60(11):110513-110513. |
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| Authors: | Cai Meng Du Hai-Feng Ren Yi-Ke and Marcus W |
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| Institution: | School of Management, Xi'an Jiaotong University, Xi'an 710049,China;Center for Administration and Complexity Science, Xi'an Jiaotong University, Xi'an 710049, China;Center for Administration and Complexity Science, Xi'an Jiaotong University, Xi'an 710049, China;School of Management, Shanxi Normal University, Linfen 041004, China;Center for Administration and Complexity Science, Xi'an Jiaotong University, Xi'an 710049, China;Morrison Institute for Population and Resource Studies,Stanford University,Stanford 94305,USA |
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| Abstract: | Entropy is a very important indicator which describes the heterogeneity of the networks. Two kinds of structure entropies, which are based on degree distribution and relative degree respectively, have some problems to describe the characteristics of network structure. Because they focus only on one of "node" or "edge" factors. In this paper, We consider the difference between "node" and "edge" to define a new network structure entropy. The theoretical analyses and the simulation experiments on regular network, random network and scale-free network prove that this new network structure entropy is more effective to reflect the characteristics of network structure, especially more reasonable to describe the sparse network and star network. |
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| Keywords: | homogeneous network scale-free network entropy |
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