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相关概念视频

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

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

100
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...
100
Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

Design Example: Calculating Safe Diameter for Wind-Exposed Disc

177
Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
177
Relative Risk01:12

Relative Risk

340
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
340
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.2K
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...
2.2K
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

600
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...
600
Unusual Results01:16

Unusual Results

3.3K
Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
Maximum unusual value =...
3.3K

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相关实验视频

Updated: Sep 9, 2025

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

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在混合交通中对道安全性进行评估的基于的多变量极值框架

Abhijnan Maji1, Indrajit Ghosh1

  • 1Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India.

Accident; analysis and prevention
|August 28, 2025
PubMed
概括

通过使用无人机录像和先进模型分析交通冲突, 它确定了高风险区域和冲突类型,以指导有针对性的安全干预.

科学领域:

  • 运输工程
  • 交通安全分析
  • 数据驱动的建模

背景情况:

  • 低收入和中等收入国家的环形车道面临着独特的安全挑战,原因是非车道交通和混合交通条件.
  • 传统的基于碰撞的分析在确定这些复杂环境的前性安全措施方面是有限的.

研究的目的:

  • 开发和验证一个数据驱动的框架,以积极识别和分类未经标志的环路上的安全关键冲突事件.
  • 整合高分辨率视频分析,先进的统计建模和机器学习以进行全面的安全评估.

主要方法:

  • 使用无人机录制的视频来提取车辆轨迹,并使用替代安全评估模型 (SSAM) 计算替代安全措施 (SSM),例如碰撞时间 (TTC) 和入侵后时间 (PET).
  • 应用多变量极值理论 (EVT) - 峰值超过值 (POT) 建模,使用Gumbel-Hougaard偶数分析SSM的联合超值,并建立特定环境的值.
  • 采用概率集群 (高斯混合模型) 进行空间冲突映射和潜伏配置分析,以按严重程度分层冲突.

主要成果:

  • 确定了关键的冲突类型:交换车道 (43%),后端 (38%) 和交叉路口 (19%),具体的热点在靠近的腿部,编织区和行人交叉路口.
  • 将冲突严重程度量化为五个级别,从轻微 (29.7%) 到严重 (7.6%),为优先级安全干预提供基础.
  • 配合EVT-POT模型有效地捕捉了SSM之间的尾部依赖性,证明了其适用于联合风险评估.
关键词:
冲突的严重程度极端价值理论 (EVT)不同类型的交通多变量偶数交通冲突技术 (TCT)无人机轨迹数据

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结论:

  • 开发的框架提供了可扩展和主动的方法,以提高在各种交通条件下的道安全性.
  • 它使实践者能够精确地确定高风险区域并实施有针对性的安全对策,超越了基于碰撞的反应方法.
  • 这项研究为改进环路设计和运营提供了宝贵的见解,特别是在资源有限的环境中.