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ORIGINAL RESEARCH article
Front. Phys.
Sec. Social Physics
Volume 12 - 2024 |
doi: 10.3389/fphy.2024.1457287
This article is part of the Research Topic Network Learning and Propagation Dynamics Analysis View all 8 articles
Analysis of differences in fossil fuel consumption in the world based on the fractal time series and complex network
Provisionally accepted- 1 Shandong Normal University, Jinan, Shandong Province, China
- 2 Zhongnan University of Economics and Law, Wuhan, China
- 3 Cornell University, Ithaca, New York, United States
Fossil fuels are indispensable energy resources. To further analyze these nonrenewable energy sources, this paper adopts complex network theory and fractal time series analysis to identify the main features of global fossil fuel consumption. The study yields several significant findings. First, applying the Hurst index to raw data reveals that all fossil fuel consumption worldwide follows a fractal time series pattern, with the highest Hurst index exceeding 0.9. This indicates that fossil fuel consumption exhibits long-term memory characteristics. Using the visibility graph method, the time series data are transformed into complex networks, showing variations in the Hurst index of the degree distribution. This allows the Hurst index of the degree distribution to be used to distinguish global fossil fuel consumption patterns and assess whether current fuel consumption randomly affects future consumption. Additionally, the paper examines coal, oil, and gas consumption in 38 countries. The visibility graph method uncovers various characteristics of the time series data, reflecting coal, oil, and gas consumption from a network perspective. It should be noted that, given that fossil fuels are necessary for China to ensure energy security and enhance international competitiveness, it is necessary to strengthen the protection
Keywords: Fossil fuel, Complex Network, Fractal time series, Hurst index, legal protection, Visibility graph
Received: 30 Jun 2024; Accepted: 03 Sep 2024.
Copyright: © 2024 Zhang, Jian and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiao Jian, Zhongnan University of Economics and Law, Wuhan, China
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