Fractal Analysis Based on Hierarchical Scaling in Complex Systems
Yanguang Chen

TL;DR
This paper explores fractal analysis in complex systems through hierarchical scaling, proposing new methods to estimate fractal dimensions and demonstrating self-similar hierarchies in urban and demographic data.
Contribution
It introduces three approaches to estimate fractal dimensions from hierarchical structures and generalizes hierarchical scaling to multifractals and self-similar curves.
Findings
Fractal systems can be described from a hierarchical perspective.
Hierarchical scaling applies to multifractals and self-similar curves.
Empirical analysis confirms self-similar hierarchy in urban and demographic data.
Abstract
A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and spatial network proved to be associated with one another. This paper is devoted to exploring the theory of fractal analysis of complex systems by means of hierarchical scaling. Two research methods are utilized to make this study, including logic analysis method and empirical analysis method. The main results are as follows. First, a fractal system such as Cantor set is described from the hierarchical angle of view; based on hierarchical structure, three approaches are proposed to estimate fractal dimension. Second, the hierarchical scaling can be generalized to describe multifractals, fractal complementary sets, and self-similar curve such as logarithmic…
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Taxonomy
TopicsComplex Network Analysis Techniques · Environmental Quality and Pollution · Complex Systems and Time Series Analysis
