Jove
Visualize
联系我们

相关概念视频

Survival Tree01:19

Survival Tree

61
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
61
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

103
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
103
Multiple Regression01:25

Multiple Regression

2.9K
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...
2.9K
Types of Reports II: Incident or Occurrence Report01:21

Types of Reports II: Incident or Occurrence Report

801
An Incident or Occurrence Report in a healthcare setting is a crucial document used to record any unexpected occurrence that may or may not have affected a patient, employee, or visitor. Such reports are critical to improving patient safety and include all details leading up to and including the event.
Purposes:
In the healthcare industry, reports play a crucial role in documenting incidents within an agency. The primary objective of these reports is to ensure patient safety, uphold the...
801
Classification of Systems-I01:26

Classification of Systems-I

169
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
169
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

631
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
631

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

How do macroscopic traffic flow parameters affect time spent in conflict on freeways? A comprehensive analysis using hazard-based duration models.

Traffic injury prevention·2025
Same author

Investigating the contributors to hit-and-run crashes using gradient boosting decision trees.

PloS one·2025
Same author

Study on ring-road incident duration based on latent class accelerated hazard model.

PloS one·2024
Same author

Identifying Risk Factors for Autos and Trucks on Highway-Railroad Grade Crossings Based on Mixed Logit Model.

International journal of environmental research and public health·2022
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jun 6, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.2K

使用基于多源数据的分类和回归树对高速公路事故持续时间的调查.

Xun Xie1, Gen Li1, Lan Wu1

  • 1College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China.

Sensors (Basel, Switzerland)
|November 27, 2024
PubMed
概括

分类和回归树 (CART) 使用高速公路传感器数据准确预测事故持续时间. 这种机器学习方法提高了应急规划和事件管理的有效性.

关键词:
汽车车上的车辆.事件持续时间事件持续时间机器学习是机器学习.多种多种来源的资源.传感器数据 传感器数据

更多相关视频

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

Published on: February 1, 2020

20.3K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.5K

相关实验视频

Last Updated: Jun 6, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.2K
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

Published on: February 1, 2020

20.3K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.5K

科学领域:

  • 交通工程是交通工程.
  • 数据挖掘 数据挖掘
  • 机器学习 机器学习

背景情况:

  • 在高速公路上发生的事件会造成重大损害和延误.
  • 有针对性的应急措施有效地减轻了事件的影响.
  • 预测事件持续时间对于有效应急响应至关重要.

研究的目的:

  • 使用分类和回归树 (CART) 数据挖掘技术预测和量化事件持续时间.
  • 将CART的预测准确性和可解释性与其他机器学习模型进行比较.
  • 制定数据驱动的规则,以进行有效的事件评估和应急规划.

主要方法:

  • 利用来自杭州高速公路 (2019-2021) 的多传感器数据.
  • 使用CART.构建了一个八层,14叶节点回归树.
  • 从CART模型中提取了14条规则,以告知应急措施.
  • 将CART与XGBoost,随机森林 (RF) 和加速失效时间 (AFT) 模型进行比较.

主要成果:

  • 与XGBoost,RF和AFT相比,CART模型显示出更高的预测准确度.
  • 该CART方法提供了强大的可解释性,捕获多达七个变量之间的相互作用.
  • 衍生规则促进了准确的事件评估和有效的应急计划实施.

结论:

  • CART是一种高效和可解释的方法,用于预测高速公路上的事故持续时间.
  • 该研究的结果支持机器学习在交通管理中的工程应用.
  • 来自CART的数据驱动洞察力可以改善事件响应并减少整体伤害.