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相关概念视频

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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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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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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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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...
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在IoRT网络中的移动意识资源分配,用于灾后通信,具有参数化的强化学习.

Homayun Kabir1, Mau-Luen Tham1, Yoong Choon Chang1

  • 1Department of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Sungai Long Campus, Kajang 43000, Malaysia.

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概括
此摘要是机器生成的。

本研究引入了一种新算法,即多通道深度Q网络 (MP-DQN),以优化灾后网络中用户设备的能源效率和吞吐量. 在自然灾害期间,MP-DQN算法增强了机器人物体的通信服务.

关键词:
深度强化学习 (DRL) 是一种深度强化学习.机器人物联网 (IoRT) 的互联网.可移动和可部署的资源单位 (MDRU)多通道深度 Q 网络 (MP-DQN)参数化的行动空间.灾难后的沟通 灾难后的沟通

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科学领域:

  • 网络工程 网络工程
  • 人工智能的人工智能
  • 灾害管理 灾害管理

背景情况:

  • 由于气候变化,自然灾害正在增加,破坏了通信基础设施.
  • 灾后管理依赖于用户设备 (UE) 通过机器人物联网 (IoRT) 进行关键操作.
  • 维护服务质量 (QoS) 和优化损坏网络中的电力消耗是一个重大挑战.

研究的目的:

  • 为了优化能源效率,UE吞吐量和服务电池 (SC) 吞吐量在IoRT支持的网络中,用于灾后情景.
  • 解决涉及功率分配和用户协会的非凸和NP-hard优化问题的复杂性.
  • 在没有先前的环境知识的情况下开发一种用于动态网络优化的新型算法.

主要方法:

  • 一个优化问题的制定,将发射功率分配和用户协会结合起来.
  • 开发一种无模型的混合动力空间算法:多通道深度Q网络 (MP-DQN).
  • 在双层异质网络 (HetsNet) 框架内考虑固定和移动用户设备.

主要成果:

  • 拟议的MP-DQN算法显著优于P-DQN和传统算法等现有方法.
  • 在奖励,平均能效,UE吞吐量和SC吞吐量方面取得了明显的改进.
  • 在具有挑战性的灾后条件下,有效优化静止和移动用户设备.

结论:

  • MP-DQN为优化灾难环境中的复杂网络参数提供了卓越的解决方案.
  • 该算法在紧急情况下为IoRT应用程序提供了增强的通信可靠性和效率.
  • 这项研究通过先进的网络优化,为更具弹性和有效的灾后管理策略做出了贡献.