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Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
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In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
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动态网络中的内部可靠性和反可靠性.

Tommaso Matteuzzi1, Franco Bagnoli1,2, Michele Baia1,2

  • 1University of Firenze, Department of Physics and Astronomy and CSDC, via G. Sansone 1, I-50019 Sesto Fiorentino, Italy.

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概括
此摘要是机器生成的。

我们为动态网络引入内部可靠性,评估单元同步. 外围单元通常是不可靠的,而中央单元往往是可靠的,这取决于合.

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科学领域:

  • 动态系统和网络理论.
  • 统计物理学的统计物理.
  • 计算神经科学是一种计算神经科学.

背景情况:

  • 在复杂的系统中,了解相互连接的单元的稳定性和行为至关重要.
  • 内部可靠性定义了网络中的复制单位如何保持其预期状态.

研究的目的:

  • 在有限动态网络中定义和量化内部可靠性.
  • 分析各种合振荡器模型中的可靠性模式,包括库拉莫托模型.
  • 调查合 (吸引力与排斥性) 对单元可靠性的影响.

主要方法:

  • 基于与原型的状态同步的内部可靠性的定义.
  • 使用横向利亚普诺夫指数进行量化.
  • 用分布式自然频率分析库拉莫托模型.
  • 检查其他合振荡器模型 (温弗里,旋转器,斯图尔特-兰多).

主要成果:

  • 在同步之前,在有吸引力的合下,外围单元是不可靠的,中央单元是可靠的.
  • 排斥性合扭转了这种模式:中央单元是不可靠的,外围单元是可靠的.
  • 大型子网络和循环神经网络表现出反可靠性,而单个单元是可靠的.
  • 库拉莫托模型中的可靠性与相位相关性有关,通过波动-消散类关系.

结论:

  • 内部可靠性是动态网络的一个可量化的属性,受单元属性和网络拓学的影响.
  • 该研究揭示了合振荡器系统的明显可靠性模式,为网络稳定提供了洞察力.
  • 结果在多个合振荡器模型中是一致的,这表明了可概括的原则.