Random Self-Similar Trees: Emergence of Scaling Laws

Random Self-Similar Trees: Emergence of Scaling Laws
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随机自相似树:缩放定律的出现

DOI:
10.1007/s10712-021-09682-0
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发表时间:
2022
影响因子:
4.6
通讯作者:
Foufoula-Georgiou, Efi
Foufoula-Georgiou, Efi
中科院分区:
地球科学1区
文献类型:
--
作者:
Kovchegov, Yevgeniy;Zaliapin, Ilya;Foufoula-Georgiou, Efi

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在复杂的系统中--地球物理的、生物的、技术的和社会经济的--等级组织和标度律的出现一直是世纪之交广泛研究的主题。虽然标度律的研究取得了很大的进展,但不同系统属性标度律的数学起源和相互关系仍然没有得到很好的解决。典型的例子是地震学的古腾堡-里克特定律和地貌学的霍顿定律。我们回顾的结果,澄清的外观,参数化,和层次系统概念化的树图的标度律的影响。最近制定的随机自相似树理论产生了一套结果的标度律的分支属性,树的分形维数,幂律分布的链接属性,不同的属性之间的幂律关系。考虑到幂律与极端事件和灾害的相关性,我们的综述为相关的理论和建模工作提供了信息,并为分层复杂系统的统一分析提供了框架。
The hierarchical organization and emergence of scaling laws in complex systems—geophysical, biological, technological, and socioeconomic—have been the topic of extensive research at the turn of the twentieth century. Although significant progress has been achieved, the mathematical origin of and relation among scaling laws for different system attributes remain unsettled. Paradigmatic examples are the Gutenberg–Richter law of seismology and Horton’s laws of geomorphology. We review the results that clarify the appearance, parameterization, and implications of scaling laws in hierarchical systems conceptualized by tree graphs. A recently formulated theory of random self-similar trees yields a suite of results on scaling laws for branch attributes, tree fractal dimension, power-law distributions of link attributes, and power-law relations between distinct attributes. Given the relevance of power laws to extreme events and hazards, our review informs related theoretical and modeling efforts and provides a framework for unified analysis in hierarchical complex systems.
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