使用和聚类来分析混乱的流浪现象
Nikodem Mierski1, Paweł Pilarczyk2
1Gdańsk University of Technology, Faculty of Applied Physics and Mathematics, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland.
Physical review. E
|December 23, 2025
概括
我们介绍了一种使用和聚类来分析动态系统中混乱漫游的新方法. 这种方法识别了系统状态和过渡,为复杂的行为提供了洞察力.
科学领域:
- 动态系统理论 动态系统理论
- 信息理论 信息理论
- 计算物理 计算物理
背景情况:
- 混乱的流浪描述了复杂的动态,系统在各种状态之间切换.
- 分析这些转变对于理解混乱系统至关重要.
- 现有的方法可能无法完全捕捉状态转换的细微差别.
研究的目的:
- 开发一种新的方法来分析混乱的流浪.
- 识别和描述准稳定状态和混乱过渡.
- 为了证明该方法在已知的混乱系统上的有效性.
主要方法:
- 利用局部的Shannon和局部的顺序来检测潜在的混乱的流浪.
- 采用基于密度的聚类算法来识别准稳定状态 (吸引力废墟) 和混乱的过渡状态.
- 使用统计测试分析居住时间和过渡动态.
主要成果:
- 通过使用度测量成功识别出容易发生混乱漫游的系统.
- 在全球合物流图 (GCMs) 中,特征吸引器废墟和混乱的过渡状态.
- 在算法上区分流动动力学的连贯和间歇阶段.
结论:
- 拟议的基于和聚类的方法提供了一个强大的框架来分析混乱的流浪.
- 这种方法有效地描述了复杂系统中状态转换的动态.
- 这些发现验证了该方法在理解像在GCM中观察到的现象等现象中的实用性.
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