THE RESILIENCE OF COMPLEX NETWORK: AN APPROACH FOR RELEVANT NODES EXTRACTION
Aldo Ramirez-Arellano and
Juan Bory-Reyes ()
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Aldo Ramirez-Arellano: Unidad Profesional Interdisciplinaria de IngenierÃa y Ciencias Sociales, y Administrativas, Instituto Politécnico Nacional, Ciudad de México 0840, México
Juan Bory-Reyes: SEPI-ESIME-Zacatenco, Instituto Politécnico Nacional, Ciudad de México 07738, México
FRACTALS (fractals), 2021, vol. 29, issue 01, 1-14
Abstract:
In this paper, a new algorithm to select the relevant nodes — those that maintain the cohesion of the network — of the complex network is presented. The experiments on most of the real complex networks show that the proposed approach outperforms centrality measures as node degree, PageRank algorithm and betweenness centrality. The rationale of the algorithm for extracting relevant nodes is to discover the self-similarity of the network. As seen in the algorithm, throughout the extraction sequence of relevant nodes, differences are advised with node degree, PageRank algorithm and betweenness centrality. Finally, empirical evidence is considered to show that complex network robustness is a nonlinear function of the small-worldness measure.
Keywords: Complex Networks; Small-World; Fractals; Resilience; Relevant Nodes (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:29:y:2021:i:01:n:s0218348x21500092
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DOI: 10.1142/S0218348X21500092
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