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相关概念视频

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

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Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
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Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
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Goodness-of-Fit Test01:16

Goodness-of-Fit Test

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The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is...
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Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

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Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
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相关实验视频

Updated: May 10, 2025

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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基于韦布尔-韦布尔分布的开源大数据系统的软件可靠性模型.

Jinyong Wang1, Haijun Geng2, Pengda Li2

  • 1School of Automation and Software Engineering, Shanxi University, Taiyuan, People's Republic of China. wjy@sxu.edu.cn.

Scientific reports
|April 26, 2025
PubMed
概括

这项研究为大数据系统引入了一种新的软件可靠性模型. 韦布尔-韦布尔模型准确地预测剩余的故障,帮助开发人员评估开源大数据软件的可靠性.

关键词:
开源大数据系统是一个开源的大数据系统.软件可靠性模型软件可靠性模型韦布尔韦布尔的分配方式

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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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相关实验视频

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科学领域:

  • 计算机科学 计算机科学
  • 软件工程 软件工程 软件工程
  • 数据科学数据科学数据科学

背景情况:

  • 大数据技术越来越多地融入生产和日常生活.
  • 大数据系统的软件可靠性是一个关键的,但研究不足的领域.
  • 开源大数据软件在后来的测试阶段往往会出现错误的增加.

研究的目的:

  • 为大数据系统提出一种新的软件可靠性模型.
  • 解决大数据软件可靠性建模和评估研究中的差距.
  • 改进开源大数据系统中剩余故障的预测.

主要方法:

  • 基于韦布尔-韦布尔分布的软件可靠性模型的开发.
  • 使用实验数据对拟议模型的经验验证.
  • 评估模型在预测剩余软件故障方面的准确性.

主要成果:

  • 建议的韦布尔-韦布尔模型在可靠性评估方面表现出有效性.
  • 实验结果证实了模型在预测剩余故障方面的准确性.
  • 该模型提供了一种可靠的方法来评估大数据开发中的软件质量.

结论:

  • 开发的模型增强了对大数据系统的软件可靠性的评估.
  • 这项研究为开发人员使用开源大数据软件提供了有价值的工具.
  • 准确的故障预测有助于提供更可靠的大数据解决方案.