Graph Concatenations to Derive Weighted Fractal Networks

Joint Authors

Zhang, Zhanqi
Xiao, Yingqing

Source

Complexity

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

Philosophy

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