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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...
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Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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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...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Machines: Problem Solving I01:22

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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
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相关实验视频

Updated: Jul 16, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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用于车辆边缘计算的任务卸载决策算法:基于深度强化学习的方法.

Wei Shi1,2, Long Chen1,2, Xia Zhu1,2

  • 1School of Computer Science and Engineering, Southeast University, Nanjing 211189, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
概括
此摘要是机器生成的。

在车辆边缘计算 (VEC) 中,高效的任务卸载是使用一种新的深度决定性政策梯度算法进行优化. 这种TODM_DDPG方法通过共同优化任务调度和卸载比例来最大限度地降低系统成本,优于现有方法.

关键词:
计算卸载卸载 计算卸载深度强化学习的学习.车辆边缘计算计算系统

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科学领域:

  • 车辆边缘计算 (VEC) 技术
  • 分布式系统 分布式系统
  • 人工智能的人工智能

背景情况:

  • 有效的任务卸载对于车辆边缘计算 (VEC) 至关重要,以满足性能需求,同时最大限度地减少资源消耗.
  • 传统的方法往往忽视了车辆的移动性,并未能完全优化服务器资源利用.
  • 现有的分布式任务卸载决策依赖于本地车辆状态,限制了整体系统效率.

研究的目的:

  • 为云端车辆三层VEC系统提出一种新的任务卸载决策算法.
  • 在车辆移动性限制下,共同优化任务安排和卸载比例.
  • 尽量减少总系统成本,考虑到延迟,能源消耗和资源竞争.

主要方法:

  • 基于深度决定性政策梯度 (TODM_DDPG) 的任务卸载决策算法的开发.
  • 使用一个演员-批评框架,其中演员网络输出确定性政策,批评网络评估行动.
  • 进行参数调整实验和比较分析,使用基线算法,如深度Q网络 (DQN) 和演员批判 (AC).

主要成果:

  • 拟议的TODM_DDPG算法有效地处理了优化问题的非凸度和高维状态空间.
  • 参数调整实验确定了算法的最佳超参数.
  • 对比实验表明,TODM_DDPG在降低系统成本方面优于基线算法.

结论:

  • TODM_DDPG算法为VEC系统中的任务卸载决策提供了一种优越的方法.
  • 与基线算法相比,拟议的方法在降低系统成本方面实现了约13%的平均性能改善.
  • 这项研究有助于在动态的车辆环境中更有效地管理资源和执行任务.