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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
645
Distributed Loads01:19

Distributed Loads

533
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
533
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
626
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

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The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
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Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

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Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
632
Ampere's Law: Problem-Solving01:31

Ampere's Law: Problem-Solving

3.6K
Ampere's law states that for any closed looped path, the line integral of the magnetic field along the path equals the vacuum permeability times the current enclosed in the loop. If the fingers of the right hand curl along the direction of the integration path, the current in the direction of the thumb is considered positive. The current opposite to the thumb direction is considered negative.
Specific steps need to be considered while calculating the symmetric magnetic field distribution...
3.6K

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Updated: Jun 28, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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在车辆边缘网络中的多用户计算卸载和资源分配算法.

Xiangyan Liu1, Jianhong Zheng1, Meng Zhang2

  • 1School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一个深度决定性政策梯度 (DDPG) 算法,以优化车辆边缘计算网络 (VECN) 的计算卸载和资源配置. 拟议的方法提高了服务质量 (QoS),并将系统延迟降低了24%至29%.

关键词:
车辆边缘计算网络 (VECN) 是指车辆边缘计算网络.计算卸载卸载 计算卸载深度强化学习的学习.资源分配的资源分配.

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科学领域:

  • * 车辆边缘计算网络 (VECN)
  • * 移动计算 移动计算
  • * 网络资源的分配.

背景情况:

  • * 车辆在VECN中的移动性引入了通道状态信息的不确定性.
  • *这种不确定性挑战了车辆边缘计算服务器 (VECS) 中计算卸载和资源分配的服务质量 (QoS).

研究的目的:

  • * 为了应对VECN中不确定的通道状态信息的挑战.
  • * 开发一个针对多用户计算卸载和资源分配的优化模型.
  • * 尽量减少总系统延迟,并确保任务执行的 QoS.

主要方法:

  • * 将问题建模为混合整数非线性编程 (MINLP) 问题.
  • * 提出了基于深度决定性政策梯度 (DDPG) 的算法,用于处理大型状态空间和混合离散/连续行动空间.
  • *将基于DDPG的方案与三个基准算法进行了比较.

主要成果:

  • *基于DDPG的方案有效地选择任务卸载模式并分配VECS资源.
  • * 确保了任务执行的 QoS,并证明了稳定性和可扩展性.
  • *与现有技术相比,总完成时间减少了24-29%.

结论:

  • * 拟议的 DDPG 算法为 VECN 中的计算卸载和资源分配提供了有效的解决方案.
  • * 该方法确保了 QoS 并减少了系统延迟,优于基线方法.
  • * 在车辆边缘计算场景中显示了显著的效率和性能改进.