焦点问题简介:复杂系统的数据驱动模型和分析。

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-03-01 DOI:10.1063/5.0263794
Johann H Martínez, Klaus Lehnertz, Nicolás Rubido
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引用次数: 0

摘要

本期特刊重点介绍复杂系统研究的最新进展,尤其侧重于数据驱动型研究。我们的社论探讨了一系列不同的主题,包括金融市场、电力定价、电网、激光、地球气候、水文学、神经元组合和大脑、生物医学、复杂网络、现实世界超图、动物行为和社交媒体。这种多样性凸显了复杂系统研究的广泛适用性。在此,我们总结了本期重点议题下发表的 47 篇论文,这些论文采用了机器学习、高阶相关性、控制理论、嵌入、信息论、对称性分析、极端事件建模、时间序列分析、分形技术、马尔可夫链和持久同源性等领域最先进或新颖的方法。这些方法大大提高了我们对复杂系统错综复杂的动力学的理解。此外,已出版的著作还展示了数据驱动方法在彻底改变复杂系统研究方面的潜力,为复杂性科学与数字数据时代交叉领域的未来研究方向和突破铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Introduction to Focus Issue: Data-driven models and analysis of complex systems.

This Focus Issue highlights recent advances in the study of complex systems, with a particular emphasis on data-driven research. Our editorial explores a diverse array of topics, including financial markets, electricity pricing, power grids, lasers, the Earth's climate, hydrology, neuronal assemblies and the brain, biomedicine, complex networks, real-world hypergraphs, animal behavior, and social media. This diversity underscores the broad applicability of complex systems research. Here, we summarize the 47 published works under this Focus Issue, which employ state-of-the-art or novel methodologies in machine learning, higher-order correlations, control theory, embeddings, information theory, symmetry analysis, extreme event modeling, time series analysis, fractal techniques, Markov chains, and persistent homology, to name a few. These methods have substantially enhanced our understanding of the intricate dynamics of complex systems. Furthermore, the published works demonstrate the potential of data-driven approaches to revolutionize the study of complex systems, paving the way for future research directions and breakthroughs at the intersection of complexity science and the digital era of data.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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