在合非线性系统中调节切换:来源,预测和控制-Minireview和焦点问题的视角
Igor Franović1, Sebastian Eydam2, Deniz Eroglu3,4
1Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia.
Chaos (Woodbury, N.Y.)
|December 2, 2024
概括
复杂的系统表现出调节切换,由于条件的变化而在状态之间过渡. 这项研究探讨了预测,检测和控制这些动态的先进方法,以防止系统故障.
科学领域:
- 复杂系统科学 复杂系统科学
- 动态系统理论 动态系统理论
- 网络科学 网络科学
背景情况:
- 政权切换是各种复杂系统中常见的现象,包括气候,生态系统,电网和神经网络.
- 了解和预测这些状态转换对于系统稳定性和防止灾难性故障至关重要.
研究的目的:
- 提供新的见解机制和预测的政权切换动态.
- 探索先进的理论和数据驱动的方法来检测和控制调节.
主要方法:
- 理论分析使用减少方法对合的随机和自适应系统.
- 数据驱动的检测方法和非反控制策略.
- 调查多个时间尺度和混乱动态对政权切换的影响.
主要成果:
- 对于具有随机和自适应组件的复杂系统,减少技术的进步.
- 用深度学习来预测电网故障和适应性策略来控制流行病的演示.
- 在模式切换中探索混乱的和异常临床周期.
结论:
- 该研究强调了新的理论和数据驱动方法来理解和管理调节切换.
- 预测,检测和控制策略的发展对于复杂系统的弹性至关重要.
- 这项工作旨在促进关于复杂性和政权动态的跨学科对话.
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