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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

678
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...
678
Reinforcement Schedules01:24

Reinforcement Schedules

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Positive reinforcement is a powerful method for teaching new behaviors to both animals and humans. B.F. Skinner demonstrated this with his experiments using rats in a Skinner box. When a rat pressed a lever, it received a food pellet. This immediate reward encouraged the rat to repeat the behavior. This method, where a reward follows every instance of the behavior, is known as continuous reinforcement. It is highly effective for establishing new behaviors quickly.
Once a behavior is learned,...
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Reinforcement01:23

Reinforcement

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Positive and negative reinforcement are key concepts in operant conditioning, a learning process where the consequences of a behavior affect the likelihood of that behavior being repeated.
Positive reinforcement occurs when a behavior is followed by the presentation of a rewarding stimulus, increasing the frequency of that behavior. For example:
282
Machines: Problem Solving I01:22

Machines: Problem Solving I

357
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.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
357
Machines: Problem Solving II01:30

Machines: Problem Solving II

336
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.
336
Transformers in Distribution System01:27

Transformers in Distribution System

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Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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面向AIoT边缘计算的优化分布式消息队列系统:一种强化学习方法

Zaipeng Xie1,2, Cheng Ji2, Lifeng Xu2

  • 1Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing 211100, China.

Sensors (Basel, Switzerland)
|July 8, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种用于AIoT边缘计算的新型分布式消息系统,增强消息排序和负载平衡. 拟议的优化算法显著提高了高同期货应用程序的系统吞吐量.

关键词:
AIoT边缘计算的边缘计算对事物的人工智能.分布式消息队列 分布式消息队列强化学习是一种强化学习方法.系统吞吐量性能表现系统吞吐量表现

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科学领域:

  • 计算机科学 计算机科学
  • 分布式系统 分布式系统
  • 人工智能的人工智能

背景情况:

  • 人工智能 (AI) 和物联网 (IoT) 在AIoT边缘计算中的集成对现有的消息队列系统提出了挑战.
  • 波动的系统条件,包括设备号码,消息大小和频率,会影响边缘服务器的实时数据处理.
  • 在AIoT环境中,存在对分离消息处理和有效管理工作负载变化的系统的需求.

研究的目的:

  • 开发一个针对AIoT边缘计算的分布式消息系统.
  • 在动态的AIoT环境中解决消息排序的关键挑战.
  • 为了提高边缘设备消息处理的可靠性和性能.

主要方法:

  • 引入一种新的分区选择算法 (PSA),以确保消息顺序和负载平衡.
  • 基于深度决定性政策梯度 (DDPG) 的分布式消息系统配置优化算法 (DMSCO) 的开发.
  • 实验评估比较DMSCO与遗传算法和随机搜索.

主要成果:

  • 该PSA有效地确保消息顺序,平衡跨经纪人集群的负载,并改善消息可用性.
  • 与传统方法相比,DMSCO算法在系统吞吐量方面取得了显著的改进.
  • 拟议的系统满足了高一致性AIoT边缘计算应用程序的苛刻要求.

结论:

  • 展示的分布式消息系统为AIoT边缘计算消息处理提供了强大的解决方案.
  • 新的PSA和DMSCO算法有助于提高性能,可靠性和可扩展性.
  • 这项工作为更高效,更有效的AIoT边缘数据处理系统提供了基础.