Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

28
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...
28
Survival Tree01:19

Survival Tree

40
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...
40
Hazard Rate01:11

Hazard Rate

75
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...
75
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

278
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...
278
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

122
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...
122
Manipulation and Analysis01:21

Manipulation and Analysis

14
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
14

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Study on energy retrofits for rural residential envelopes in Northwest China.

Scientific reports·2025
Same author

[Research of Herba Artemisiae Scoporiae inhibits the hepatic lipotoxicity].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2009
Same author

Bromine chloride as an oxidant to improve elemental mercury removal from coal-fired flue gas.

Environmental science & technology·2009
Same author

Antidepressant-like effects of 3,6'-disinapoyl sucrose on hippocampal neuronal plasticity and neurotrophic signal pathway in chronically mild stressed rats.

Neurochemistry international·2009
Same author

Fuzheng Huayu recipe and vitamin E reverse renal interstitial fibrosis through counteracting TGF-beta1-induced epithelial-to-mesenchymal transition.

Journal of ethnopharmacology·2009
Same author

Association of brain-derived neurotrophic factor genetic Val66Met polymorphism with severity of depression, efficacy of fluoxetine and its side effects in Chinese major depressive patients.

Neuropsychobiology·2009

Related Experiment Video

Updated: May 12, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K

Analysis of collapse risks under cut and cover method based on multi-state fuzzy Bayesian network.

Ping Liu1, Xueqiang Jin1, Yongtao Shang2

  • 1School of Civil Engineering, Lanzhou University of Technology, Lanzhou, China.

Plos One
|May 7, 2025
PubMed
Summary

Metro construction using the cut and cover method faces frequent collapse risks. This study developed a fuzzy Bayesian network to predict collapse probability and identify key causal factors, aiding safety decisions.

More Related Videos

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.0K

Related Experiment Videos

Last Updated: May 12, 2025

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.0K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.0K

Area of Science:

  • Civil Engineering
  • Risk Management
  • Construction Safety

Background:

  • Collapse accidents in metro station construction using the cut and cover method are frequent, causing significant damage and casualties.
  • Research on collapse risks in this construction method is limited in China, highlighting a critical knowledge gap.

Purpose of the Study:

  • To investigate and quantify collapse risks in cut and cover metro station construction.
  • To develop a predictive model for assessing collapse probabilities and identifying key causal factors.

Main Methods:

  • Utilized a multi-state fuzzy Bayesian network model, incorporating 9 intermediate and 16 bottom factors identified through accident analysis.
  • Employed triangular fuzzy functions for data fuzzification and conditional probabilities to represent node relationships.
  • Incorporated an expert credibility-based survey for accurate node failure probability assessment.

Main Results:

  • The developed model predicted no-failure, moderate-failure, and severe-failure probabilities of 71%, 19%, and 10% for a case project.
  • Sensitivity analyses identified critical causal factors contributing to moderate and severe collapse risks.

Conclusions:

  • The fuzzy Bayesian network method effectively predicts collapse risk probabilities and identifies key causal factors in cut and cover construction.
  • This approach offers valuable decision support for enhancing safety and reducing collapses in metro station projects.