Reconstruction of networks from one-step data by matching positions

Jianshe Wu, Ni Dang and Yang Jiao

Physica A: Statistical Mechanics and its Applications, 2018, vol. 497, issue C, 118-125

Abstract: It is a challenge in estimating the topology of a network from short time series data. In this paper, matching positions is developed to reconstruct the topology of a network from only one-step data. We consider a general network model of coupled agents, in which the phase transformation of each node is determined by its neighbors. From the phase transformation information from one step to the next, the connections of the tail vertices are reconstructed firstly by the matching positions. Removing the already reconstructed vertices, and repeatedly reconstructing the connections of tail vertices, the topology of the entire network is reconstructed. For sparse scale-free networks with more than ten thousands nodes, we almost obtain the actual topology using only the one-step data in simulations.

Keywords: Network reconstruction; Topology of network; Time series data; Reconstruction algorithm; Matching positions (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:497:y:2018:i:c:p:118-125

DOI: 10.1016/j.physa.2018.01.011

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