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A New Method of Quantifying the Complexity of Fractal Networks

Faculty of Information Studies, 8000 Novo Mesto, Slovenia
Department of Structural Mechanics and Analysis, Technical University Berlin, 10623 Berlin, Germany
Štore Steel Ltd., Železarska cesta 3, 3220 Štore, Slovenia
Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia
Department of Electric, Electronics and Computer Engineering, University of Catania, 95125 Catania, Italy
Author to whom correspondence should be addressed.
Academic Editor: Sergei Fedotov
Fractal Fract. 2022, 6(6), 282;
Received: 25 March 2022 / Revised: 15 May 2022 / Accepted: 16 May 2022 / Published: 24 May 2022
(This article belongs to the Special Issue Application of Fractals in Networks and Public Transport Systems)
There is a large body of research devoted to identifying the complexity of structures in networks. In the context of network theory, a complex network is a graph with nontrivial topological features—features that do not occur in simple networks, such as lattices or random graphs, but often occur in graphs modeling real systems. The study of complex networks is a young and active area of scientific research inspired largely by the empirical study of real-world networks, such as computer networks and logistic transport networks. Transport is of great importance for the economic and cultural cooperation of any country with other countries, the strengthening and development of the economic management system, and in solving social and economic problems. Provision of the territory with a well-developed transport system is one of the factors for attracting population and production, serving as an important advantage for locating productive forces and providing an integration effect. In this paper, we introduce a new method for quantifying the complexity of a network based on presenting the nodes of the network in Cartesian coordinates, converting to polar coordinates, and calculating the fractal dimension using the ReScaled ranged (R/S) method. Our results suggest that this approach can be used to determine complexity for any type of network that has fixed nodes, and it presents an application of this method in the public transport system. View Full-Text
Keywords: fractal; network; complexity; Hurst exponent H; public transport fractal; network; complexity; Hurst exponent H; public transport
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MDPI and ACS Style

Babič, M.; Marinković, D.; Kovačič, M.; Šter, B.; Calì, M. A New Method of Quantifying the Complexity of Fractal Networks. Fractal Fract. 2022, 6, 282.

AMA Style

Babič M, Marinković D, Kovačič M, Šter B, Calì M. A New Method of Quantifying the Complexity of Fractal Networks. Fractal and Fractional. 2022; 6(6):282.

Chicago/Turabian Style

Babič, Matej, Dragan Marinković, Miha Kovačič, Branko Šter, and Michele Calì. 2022. "A New Method of Quantifying the Complexity of Fractal Networks" Fractal and Fractional 6, no. 6: 282.

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