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相关概念视频

Maximum Power Transfer01:16

Maximum Power Transfer

396
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
396
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

178
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.
178
Energy Budgets00:51

Energy Budgets

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Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
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Energy to Drive Translocation01:37

Energy to Drive Translocation

2.1K
Mitochondrial protein import is powered by two distinct energy sources: ATP hydrolysis and electrochemical potential across the inner membrane. Newly synthesized precursors are bound by cytosolic chaperones of the Hsp70 family, which guide them to the import receptors on the mitochondrial surface. Utilizing the energy of ATP hydrolysis, Hsp70 chaperones transfer these precursors to the TOM receptors on the mitochondrial outer membrane.
Generally, polypeptides are unfolded by two distinct...
2.1K
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.5K
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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Energy Conservation and Bernoulli's Equation01:16

Energy Conservation and Bernoulli's Equation

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Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
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相关实验视频

Updated: Sep 9, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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一个基于ML的资源分配方案,用于5GNR的能源优化

Xiao Yao1, Antonio Pérez Yuste1

  • 1ETSI Sistemas de Telecomunicación, Universidad Politécnica de Madrid, 28031 Madrid, Spain.

Sensors (Basel, Switzerland)
|August 28, 2025
PubMed
概括

这项研究介绍了优化5G新无线电能耗的机器学习框架. 通过预测性资源管理,减少了40%以上的能源消耗,同时确保了服务质量.

科学领域:

  • 电信工程
  • 计算机科学
  • 人工智能

背景情况:

  • 5G新无线电 (5G NR) 网络面临着日益增长的能源需求.
  • 有效的能源管理对于可持续的网络运行至关重要.
  • 保持服务质量 (QoS) 与节能是一项重大挑战.

研究的目的:

  • 为5G NR提出并验证基于机器学习的能源优化框架.
  • 减少5GNR基站的能源消耗.
  • 确保节能策略不会损害基本的质量标准.

主要方法:

  • 使用分类和回归树 (CART) 算法进行预测性负载预测.
  • 基于预测的网络负载实现动态单元资源重新配置.
  • 模拟带间NR-NR双连接 (DC) 网络布局进行验证.

主要成果:

  • 实现了42.3%的能源消耗降低.
  • 在第三代合作项目 (3GPP) 规定的门内保持服务质量 (QoS) 参数.
  • 通过模拟网络案例研究量化验证拟议的模型.

结论:

关键词:
在5G RAN中在RRC能源效率机器学习资源分配

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  • 拟议的机器学习框架有效优化了5G NR网络的能源消耗.
  • 通过预测性负载预测驱动的动态电池资源重新配置是一种可行的节能策略.
  • 在不影响网络性能的情况下,CART算法提供了一种可靠的方法来实现显著的能源减少.