使用因果波,因果信息,方程重建和其他技术,推断给定系统的变量之间的合
Sylvain Mangiarotti1, Mathis Neuhauser1,2, Ludovic Arnaud1
1University of Toulouse/UT-CNES-CNRS-IRD-INRAE, Centre d'Études Spatiales de la Biosphère, 18 avenue Édouard Belin, 31401 Toulouse, France.
从现实数据中推断定向合是具有挑战性的. 双变量建模和方程重建技术有效地检测动态系统中的因果关系,在各种条件下优于其他方法.
科学领域:
- 动态系统和混沌理论
- 时间序列分析时间序列分析
- 因果关系 推断 推理
背景情况:
- 从观测时间序列推断定向合是动态系统中的一个复杂问题.
- 现有的方法往往与现实世界的数据扎,特别是随机扰动和低相关性.
研究的目的:
- 评估各种因果推理技术在确定性和部分确定性系统上的能力.
- 确定强大的方法来检测复杂系统中直接和间接的因果关系.
主要方法:
- 模拟两个合的3D混乱子系统 (散流和保守) 的模拟,合强度不同.
- 技术的应用和评估:相关性,相互信息,格兰杰因果关系,波形连贯性,双变量全球建模和方程重建.
- 测试来自塞山河流域的观测地下水位数据.
主要成果:
- 大多数测试的技术在检测直接合时表现不佳,对抗噪声和弱合的强度不佳.
- 双变量全球建模和方程重建技术在推断因果关系方面表现出卓越的有效性.
- 在噪音条件下检测弱双向合器尤其具有挑战性.
结论:
- 双变量建模和方程重建是复杂动态系统中因果推理最有前途的方法.
- 这项研究强调了用真实世界,杂的时间序列数据推断因果关系的挑战.
- 在塞山河流域的地下水位中发现了决定性,复杂的合.
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