Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Survival Tree01:19

Survival Tree

369
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
369
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

268
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
268
Responses to Drought and Flooding02:41

Responses to Drought and Flooding

11.9K
Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
11.9K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.1K
Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

20.1K
Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
20.1K
Rapidly Varying Flow01:24

Rapidly Varying Flow

398
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
398

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Ordinal patterns for characterization of transition to extreme events.

Chaos (Woodbury, N.Y.)·2026
Same author

Lyapunov exponents estimation via automatic differentiation: A modern approach inspired by machine learning.

Chaos (Woodbury, N.Y.)·2025
Same author

Extreme events in gene regulatory networks with time-delays.

Scientific reports·2025
Same author

Supertransient Chaos in a Single and Coupled Liénard Systems.

Entropy (Basel, Switzerland)·2024
Same author

Extreme events and extreme multistability in a nearly conservative system.

Chaos (Woodbury, N.Y.)·2024
Same author

Self-assembled molecular network with waterwheel-like architecture: experimental and theoretical evaluation toward electron transport capabilities for optoelectronic devices.

Physical chemistry chemical physics : PCCP·2024

相关实验视频

Updated: Jan 8, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.4K

学习过渡到极端事件使用储库计算的学习.

Ajit Mahata1, S Leo Kingston2,3, Subrata Ghosh1

  • 1Technical University of Lodz, Division of Dynamics, Stefanowskiego 1/15, 90-924 Lodz, Poland.

Physical review. E
|December 23, 2025
PubMed
概括
此摘要是机器生成的。

这项研究使用储库计算机器学习来预测动态系统中的极端事件. 该方法准确地预测事件幅度和过渡点,保持统计属性.

更多相关视频

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

相关实验视频

Last Updated: Jan 8, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

1.4K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

科学领域:

  • 非线性动力学是一种非线性动力学.
  • 机器学习是机器学习.
  • 复杂的系统复杂的系统.

背景情况:

  • 动态系统中的极端事件很难预测,因为时间不规则和幅度大.
  • 准确预测振幅和时间仍然是一个重大挑战.

研究的目的:

  • 应用储水库计算机器学习来预测范式动态系统中的极端事件.
  • 评估机器学习在预测事件过渡,振幅和统计属性的有效性.
  • 为了确定预测的最佳输入参数,使用预测地平线和平均平方误差等指标.

主要方法:

  • 使用部分或完整的系统变量信息,采用了水库计算机器学习.
  • 该方法在强迫的Liénard系统,结合的FitzHugh-Nagumo模型和隐藏的吸引力模型上进行了测试.
  • 来自强制Liénard电路的数值数据和实时实验数据用于训练和验证.

主要成果:

  • 机器学习模型成功地通过Pomeau-Manneville和危机引起的间歇性预测了过渡点到极端事件.
  • 极端事件的吸引力和统计性质 (事件分布,事件间隔) 被准确地复制.
  • 时间进化预测仅限于几次Lyapunov时间,但极端事件的幅度被保留或准确地预测.

结论:

  • 储计算为预测复杂动态系统中的极端事件提供了一种有希望的方法.
  • 该方法有效地捕捉了极端事件的动态和统计特征,特别是间歇性.
  • 虽然短期时间演变预测是有限的,但振幅预测和过渡点预测显示出高准确度.