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相关概念视频

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

184
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.
184
Evolutionary Psychology01:20

Evolutionary Psychology

443
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
443
Energy and Power Signals01:17

Energy and Power Signals

609
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
609
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.8K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.8K
Electrical Energy01:10

Electrical Energy

1.3K
Using electric appliances for a longer period of time consumes more electrical energy and results in a higher electric bill. The energy produced by the transfer of electrons from one point to another is known as electrical energy. If power is delivered at a constant rate, the electrical energy can be defined as the product of power used by the device for a period of time. The energy unit on electric bills is the kilowatt-hour, where one kilowatt-hour is equivalent to 3.6 × 106 joules.
1.3K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

764
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...
764

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相关实验视频

Updated: Sep 16, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

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使用开发的人类进化优化算法和Xception神经网络进行电力使用预测.

Dongxian Yu1, Di Wu2, Chongyang Liao3

  • 1College of Modern Information technology, Henan Polytechnic, Zhengzhou, 450046, Henan, China.

Scientific reports
|July 9, 2025
PubMed
概括
此摘要是机器生成的。

这项研究提出了一种新的方法,用于预测使用电力的发达人类进化优化 (DHEO) 算法和Xception神经网络 (Xception-NN). 节能策略显著减少了消耗,特别是在工业部门.

关键词:
开发了人类进化优化 (DHEO) 算法.电力消耗 电力消耗优化优化 优化优化预测 预测 预测Xception-NNNNNNNNNNNXception-NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN

相关实验视频

Last Updated: Sep 16, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K

科学领域:

  • 人工智能的人工智能
  • 能源系统 能源系统
  • 计算优化计算优化

背景情况:

  • 准确的电力使用预测对于能源电网管理和资源分配至关重要.
  • 传统的预测模型经常在能源消耗数据中与复杂的非线性模式作斗争.
  • 深度学习和进化算法为提高预测准确性提供了潜力.

研究的目的:

  • 引入一种新的混合模型,将Xception神经网络 (Xception-NN) 与开发的人类进化优化 (DHEO) 算法相结合,用于增强电力使用预测.
  • 在基线和节能场景下分析电力消耗模式.
  • 确定节能措施对最有影响的行业.

主要方法:

  • 开发一个修改的Xception神经网络 (Xception-NN) 深度学习模型,用于时间序列的电力消耗数据.
  • 应用开发的人类进化优化 (DHEO) 算法来改进Xception-NN参数以改进模式识别.
  • 在基线 (BL) 和节能 (EC) 场景下模拟电力消耗,考虑天气,人口统计和经济等因素.

主要成果:

  • DHEO-Xception-NN模型在捕捉电力消耗的复杂依赖性和模式方面表现出更高的准确性.
  • 节能 (EC) 场景导致电力消耗总体显著减少6.54%.
  • 在EC情景下,工业部门的电力消耗下降幅度最大.

结论:

  • 混合DHEO-Xception-NN方法为能源公司提供了一种强大的工具,以提高需求预测和优化能源生产.
  • 节能举措可以大幅减少电力使用,对不同经济部门产生有针对性的影响.
  • 这项研究为决策者和公用事业提供商提供了有价值的见解,旨在提高能源效率和管理未来的能源需求.