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相关概念视频

Hazard Rate01:11

Hazard Rate

376
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
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Multiple Regression01:25

Multiple Regression

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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Determination of Expected Frequency01:08

Determination of Expected Frequency

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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
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Regression Analysis01:11

Regression Analysis

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Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
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Introduction To Survival Analysis01:18

Introduction To Survival Analysis

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Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
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相关实验视频

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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通过使用回归模型分析利用率和成本,评估建筑设备事故风险.

Minwoo Song1, Jaewook Jeong1, Jaehyun Lee2

  • 1Department of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.

Risk analysis : an official publication of the Society for Risk Analysis
|December 23, 2025
PubMed
概括

这项研究开发了一种回归模型,使用成本和利用数据来预测建筑设备事故. 该模型将挖掘机确定为具有最高死亡风险的挖掘机,有助于安全管理.

关键词:
事故发生的风险 事故发生的风险建筑设备 建筑设备回归分析是一种回归分析.使用率利用率使用率.

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科学领域:

  • 建设管理建设管理.
  • 职业安全与健康问题 职业安全与健康问题
  • 风险分析 风险分析

背景情况:

  • 建筑设备是必不可少的,但会带来重大事故风险.
  • 技术进步增加了设备需求,并引入了新的安全挑战.
  • 对事故可能性的定量分析对于有效的安全管理至关重要.

研究的目的:

  • 开发用于建筑设备的定量事故预测模型.
  • 分析利用率,分包商类型和成本对事故发生概率的影响.
  • 为加强安全管理和投资决策提供一个工具.

主要方法:

  • 数据收集和建筑设备使用的分类.
  • 计算每小时运营成本 (HOC) 和整体建设成本.
  • 在回归分析中应用数据增强技术 (多变量正常和波桑分布).

主要成果:

  • 对于大多数设备类型,回归分析给出了高的R平方值 (>0.6).
  • 垃圾车的死亡率是历史上最高的.
  • 预测模型显示,挖掘机预计死亡人数最高.

结论:

  • 拟议的模型有效地根据运营和建设成本对风险组进行分类.
  • 该模型为安全管理中的现场应用提供了实际框架.
  • 这项研究支持了建筑设备安全法规和投资策略的制定.