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相关概念视频

Weighted Mean00:57

Weighted Mean

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While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
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Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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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
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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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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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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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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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相关实验视频

Updated: Jan 10, 2026

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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一个改进的加权平均算法与基于云的风险意识的随机模型用于建筑能源优化.

Suraparb Keawsawasvong1, Thira Jearsiripongkul2, Mohammad Khajehzadeh3

  • 1Research Unit in Sciences and Innovative Technologies for Civil Engineering Infrastructures, Department of Civil Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12120, Thailand.

Scientific reports
|November 27, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种基于云计算理论的模型,用于优化建筑能耗,使用改进的加权平均算法 (IWAA) 来最大限度地降低年度能耗 (AEC),同时考虑到效率的不确定性.

关键词:
建筑能效优化 建筑能效优化基于云的风险意识的随机模型.动态重量更新机制动态重量更新机制改进了加权平均算法.

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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科学领域:

  • 建筑能效优化 建筑能效优化
  • 随机模型的建模
  • 云理论应用 云理论应用

背景情况:

  • 建筑的能源消耗是全球能源使用的一个重要因素.
  • 冷却和加热效率的不确定性对能源优化构成风险.
  • 现有的优化算法可能无法充分处理参数变化.

研究的目的:

  • 开发基于云理论的随机模型,用于建筑能源优化.
  • 通过解决环境参数变化,最大限度地降低办公楼的年度能源消耗 (AEC).
  • 引入一个改进的加权平均算法 (IWAA) 与一个动态加权更新机制.

主要方法:

  • 提出了一个基于云理论的随机模型.
  • 开发了带有动态权重更新机制的改进权重平均算法 (IWAA).
  • 在不同天气条件下对IWAA与基准函数以及建筑能源优化场景进行了评估.

主要成果:

  • 与WAA,PSO和WOA相比,IWAA表现优越,在较低的AEC中产生更稳定和更一致的结果.
  • 通过云理论将不确定性纳入,提高了能源预测的现实性和可信性.
  • 该模型有效地平衡了勘探-开采权衡,以提高优化.

结论:

  • 拟议的IWAA提供了一个强有力的方法来构建能源优化,有效地管理不确定性.
  • 云理论集成提高了动态环境中能源预测的可靠性.
  • 开发的模型显示了可持续和节能建筑设计的巨大潜力.