相关实验视频
Updated: May 27, 2025

05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
2.0K
可解释组合学习在工作场所风险评估中的应用:以中国煤炭行业为例
QiFei Wang1, YiHan Zhao1,2, JunLong Wang1
1School of Mechanical-Electronic and Automobile Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China.
Risk analysis : an official publication of the Society for Risk Analysis
|February 21, 2025
概括
本研究引入了使用机器学习和SHAP分析的新工作场所风险评估框架. 它准确地确定了关键的风险因素,提高了安全性和预防职业伤害.
科学领域:
- 职业安全与健康问题 职业安全与健康问题
- 人工智能在风险管理中的应用
- 数据科学用于工业安全
背景情况:
- 机器学习对复杂的风险评估有希望,但缺乏可解释性.
- 现有的模型很难解释工作场所危险的非线性变化.
- 准确的风险评估对于预防职业伤害和损失至关重要.
研究的目的:
- 开发一个新的工作场所风险评估框架.
- 提高机器学习模型在风险评估中的可解释性和性能.
- 确定影响工作场所风险水平的关键属性.
主要方法:
- 利用组合学习算法进行风险评估.
- 应用SHAP (夏普利添加式解释) 分析,以获得模型的可解释性.
- 使用来自中国煤炭企业的事故数据验证了框架.
主要成果:
- 开发的框架准确地评估了工作场所的风险,准确度高达98.3%.
- SHAP分析成功地确定了导致风险的关键属性.
- 该模型提供了对决策过程的洞察,提高了可解释性.
结论:
- 在集体学习中解决可解释性可以提高工作场所风险评估的准确性.
- 该框架有效地确定了风险水平确定的因果关系.
- 这种方法为预防事故和减少职业伤害提供了有价值的策略.
相关概念视频
Hazard Rate
83
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...
83
Statistical Methods for Analyzing Epidemiological Data
284
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
284
Steps in Outbreak Investigation
102
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
102
Actuarial Approach
54
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
54
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
111
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
111
Survival Tree
51
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...
Building a Survival Tree
Constructing a...
51

