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Graph Concatenations to Derive Weighted Fractal Networks
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Given an initial weighted graph G0, an integer m>1, and m scaling factors f1,…,fm∈0,1, we define a sequence of weighted graphs Gkk=0∞ iteratively.
Provided that Gk−1 is given for k≥1, we let Gk−11,…,Gk−1m be m copies of Gk−1, whose weighted edges have been scaled by f1,…,fm, respectively.
Then, Gk is constructed by concatenating G0 with all the m copies.
The proposed framework shares several properties with fractal sets, and the similarity dimension dfract has a great impact on the topology of the graphs Gk (e.g., node strength distribution).
Moreover, the average geodesic distance of Gk increases logarithmically with the system size; thus, this framework also generates the small-world property.
American Psychological Association (APA)
Zhang, Zhanqi& Xiao, Yingqing. 2020. Graph Concatenations to Derive Weighted Fractal Networks. Complexity،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1142125
Modern Language Association (MLA)
Zhang, Zhanqi& Xiao, Yingqing. Graph Concatenations to Derive Weighted Fractal Networks. Complexity No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1142125
American Medical Association (AMA)
Zhang, Zhanqi& Xiao, Yingqing. Graph Concatenations to Derive Weighted Fractal Networks. Complexity. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1142125
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142125