在BTW和Manna沙堆中比较预测效率
Denis Sapozhnikov1, Alexander Shapoval2, Mikhail Shnirman3
1HSE University, Myasnitskaya 20, Moscow, 101000, Russia.
Scientific reports
|November 25, 2024
概括
在自我组织的关键性模型中预测极端事件是可以通过观察不活动时期来实现的. 这项研究表明,Manna模型允许预测,与Bak-Tang-Wiesenfeld模型不同,基于格子长度缩放.
科学领域:
- 复杂的系统复杂的系统.
- 统计物理 统计物理
- 计算物理 计算物理
背景情况:
- 自组织关键性 (SOC) 理论认为,某些系统自然演变为关键状态.
- 在SOC系统中,极端事件往往先于活动减少的时期,这表明潜在的可预测性.
- 巴克-坦格-维森菲尔德 (BTW) 和曼娜模型是用于研究SOC现象的正规例子.
研究的目的:
- 在BTW和Manna模型中调查极端事件的可预测性.
- 分析这些SOC模型中的预测效率如何与格子长度相变.
- 为了确定基于不活动的预测是否在不同的SOC普遍性类别中普遍适用.
主要方法:
- 在不同长度的正方形格子上模拟了BTW和Manna模型.
- 使用算法预测系统活动下降后发生的大事件.
- 通过使用权力定律函数将事件大小与格子长度相关,量化预测效率.
主要成果:
- 两个模型的预测效率都随着事件大小和格子长度而普遍变化.
- 马纳模型的权力定律指数为2.75,与已知的缩放行为一致.
- BTW模型显示3的最大权力定律指数,表明不同的缩放性质.
- 在热力学极限中,Manna模型显示基于不活动的可预测性,而BTW模型则没有.
结论:
- 在SOC模型中极端事件的可预测性取决于它们的普遍性类.
- 马纳模型的缩放表明可靠的预测是可能的,而BTW模型的缩放表明局限性.
- 普遍性类的差异解释了基于先前不活动的不同预测能力.
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