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复杂网络中多源定位的 Pearson 算法定位能力。

The locatability of Pearson algorithm for multi-source location in complex networks.

机构信息

School of Information, Beijing Wuzi University, Beijing, 101149, People's Republic of China.

College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua, 321004, People's Republic of China.

出版信息

Sci Rep. 2023 Apr 7;13(1):5692. doi: 10.1038/s41598-023-32832-w.

Abstract

We study locating propagation sources in complex networks. We proposed an multi-source location algorithm for different propagation dynamics by using sparse observations. Without knowing the propagation dynamics and any dynamic parameters, we can calculate node centrality based on the character that positive correlation between inform time of nodes and geodesic distance between nodes and sources. The algorithm is robust and have high location accuracy for any number of sources. We study locatability of the proposed source location algorithm and present a corresponding strategy to select observer nodes based on greedy algorithm. All simulations on both model and real-world networks proved the feasibility and validity of this algorithm.

摘要

我们研究在复杂网络中定位传播源。我们提出了一种利用稀疏观测值来针对不同传播动力学进行多源定位的算法。在不知道传播动力学和任何动态参数的情况下,我们可以根据节点信息时间和节点与源之间的测地距离之间的正相关性,基于节点中心性来计算。该算法具有鲁棒性,对于任何数量的源都具有高精度的定位能力。我们研究了所提出的源定位算法的可定位性,并提出了一种基于贪婪算法选择观测节点的相应策略。在模型和真实网络上的所有仿真都证明了该算法的可行性和有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c256/10082217/5776dc51ba1d/41598_2023_32832_Fig1_HTML.jpg

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