当前位置: X-MOL 学术J. Stat. Mech. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Identifying influential nodes to enlarge the coupling range of pinning controllability
Journal of Statistical Mechanics: Theory and Experiment ( IF 2.4 ) Pub Date : 2020-09-01 , DOI: 10.1088/1742-5468/abacb4
Ming-Yang Zhou , Rong-Qin Xu , Xiao-Yu Li , Hao Liao

Choosing influential nodes is crucial for pinning complex networks. However, most previous works only optimize the eigenratio of the Laplacian relevant matrices. Here, we address the problem of how to optimize the coupling range of a pinned system. Based on the matrix perturbation theory, we proposed a method to choose optimal pinning nodes. The detected pinning nodes could maximize the coupling range and outperform the classical methods. Besides, compared with the state of the art methods, the proposed method has high robustness and performs well across different networks, whereas the performance of previous methods fluctuates largely in different networks. Simulation results in real networks demonstrate the effectiveness of the proposed method.

中文翻译:

识别有影响力的节点以扩大钉扎控制能力的耦合范围

选择有影响力的节点对于固定复杂网络至关重要。然而,大多数先前的工作仅优化了拉普拉斯相关矩阵的本征比。在这里,我们解决了如何优化固定系统的耦合范围的问题。基于矩阵扰动理论,提出了一种选择最优钉扎节点的方法。检测到的钉扎节点可以最大化耦合范围,并且性能优于经典方法。此外,与现有技术方法相比,所提出的方法具有较高的鲁棒性,并且在不同的网络中表现良好,而先前方法的性能在不同的网络中波动很大。真实网络中的仿真结果证明了该方法的有效性。
更新日期:2020-09-02
down
wechat
bug