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相关概念视频

Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

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Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
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Confidence Coefficient01:24

Confidence Coefficient

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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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Compacting Factor test01:22

Compacting Factor test

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The compacting factor test is a method used to assess the workability of concrete. It is  especially suitable for concrete mixes containing aggregates up to one and a half inches in size. This test involves specialized equipment consisting of two truncated cone-shaped hoppers and a cylinder, all with polished interior surfaces to minimize friction.
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
164
Mean Absolute Deviation01:13

Mean Absolute Deviation

2.6K
The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...
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Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
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Measurement of Air Content in Concrete01:23

Measurement of Air Content in Concrete

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Air content measurement in concrete is critical for ensuring structural integrity and durability of concrete structures, especially in environments prone to severe weather conditions. Accurate air content analysis optimizes concrete's resistance to freeze-thaw cycles and enhances its workability and strength. Several methods are standardized under ASTM guidelines to measure the air content in fresh concrete, each suitable for different concrete types and conditions.
The pressure method,...
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相关实验视频

Updated: Jul 10, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

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云网络融合能力评估指数方法的研究.

Tengteng Ma1, Yuanmou Chen2, Haobin Wang2

  • 1Strategy Development Institute, China Telecom Corporation Limited Beijing Research Institute, Beijing, 102209, China. matt1@chinatelecom.cn.

Scientific reports
|November 21, 2023
PubMed
概括

本研究引入了云网络融合的新指数系统,增强了评估稳定性,并为未来的发展提供了关键的参考权重. 改进的方法确保可靠的云网络融合评估.

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Last Updated: Jul 10, 2025

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科学领域:

  • 计算机科学 计算机科学
  • 网络工程 网络工程
  • 系统工程 系统工程

背景情况:

  • 目前的云网络融合缺乏一个强大的指数系统,用于指导和开发.
  • 选择和评估云网络融合指数是一个复杂的挑战,需要专门的方案.

研究的目的:

  • 为云网络融合提出一个改进的索引选择和评估方案.
  • 提高指数评估的稳定性和可靠性,特别是在存在异常数据的情况下.

主要方法:

  • 开发了一种改进的分析层次过程 (i-AHP) 用于索引选择.
  • 利用专家经验,几何平均值和最小方程来开发方案.
  • 引入了一种改进的加权最小方形方法 (WLSM),用于指数评估稳定性.

主要成果:

  • 在WLSM表现出优越的稳定性指数评估,即使有异常的数据.
  • 拟议的i-AHP和WLSM计划有效地避免了数据波动引起的权重偏差.
  • 来自WLSM的指数权重为云网络融合发展提供了有价值的参考.

结论:

  • 开发的i-AHP和WLSM提供了一种更稳定,更可靠的方法来评估云网络融合.
  • 拟议的方案解决了在这个领域需要一个可测量和可评估的指数系统的需求.
  • 这项研究为推进云网络融合基础设施提供了实际指导和参考权重.