• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

运用ISM-ANP-SD 组合模型探究煤矿安全系统影响因素的作用机制及干预策略。

Using the ISM-ANP-SD combination model to explore the mechanism and intervention strategies of influencing factors of coal mine safety system.

机构信息

School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China.

College of Information and Management Science, Henan Agricultural University, Zhengzhou, China.

出版信息

Front Public Health. 2022 Nov 23;10:1053298. doi: 10.3389/fpubh.2022.1053298. eCollection 2022.

DOI:10.3389/fpubh.2022.1053298
PMID:36504987
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9731289/
Abstract

BACKGROUND

With the intelligent construction of coal mines, the number of coal mine accidents is gradually decreasing, but the complexity of accidents is increasing. Understanding the interaction mechanism among the influencing factors of the coal mine safety system is an essential part of improving and enhancing the safety of the coal mine system.

METHODS

The descriptive, structural model-network hierarchical analysis (ISM-ANP) was used to explore the interaction between the factors influencing the coal mine safety system and determine each factor's importance. A system dynamics simulation model was constructed to clarify the mechanism of each factor's effect on the safety system.

RESULTS

The results show that Individual miners' factors directly influence coal mine system safety, organizational management factors, and group factors indirectly influence system safety and play the role of macro regulation. The intelligent system is the most profound factor influencing system safety. There are apparent differences in the influence of different subsystems on system safety, with organizational management having the most significant influence on system safety, followed by individual miners and group factors, and intelligent system factors and external environmental factors having a more negligible influence on system safety.

CONCLUSION

There is a complex interaction between the factors affecting the safety of the coal mine system, and there are apparent differences in the influence of different subsystems on the safety level of the coal mine system. This study puts forward the intervention strategy to improve the safety of the coal mine system, which provides theoretical support and method guidance for preventing coal mine accidents and improving the safety level of the coal mine system.

摘要

背景

随着煤矿智能化建设的推进，煤矿事故数量逐渐减少，但事故的复杂性却在增加。了解煤矿安全系统影响因素之间的相互作用机制是改善和提高煤矿系统安全性的重要组成部分。

方法

采用描述性、结构模型-网络层次分析法（ISM-ANP）来探索影响煤矿安全系统的因素之间的相互作用关系，并确定各因素的重要性。构建系统动力学仿真模型，阐明各因素对安全系统的作用机制。

结果

结果表明，个体矿工因素直接影响煤矿系统安全，组织管理因素和群体因素间接影响系统安全，发挥宏观调控作用。智能系统是影响系统安全最深刻的因素。不同子系统对系统安全的影响存在明显差异，其中组织管理对系统安全的影响最大，其次是个体矿工和群体因素，智能系统因素和外部环境因素对系统安全的影响较小。

结论

影响煤矿系统安全的因素之间存在复杂的相互作用关系，不同子系统对煤矿系统安全水平的影响存在明显差异。本研究提出了提高煤矿系统安全性的干预策略，为预防煤矿事故和提高煤矿系统安全水平提供了理论支持和方法指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/14c7c507c3de/fpubh-10-1053298-g0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/b9846edd2a2b/fpubh-10-1053298-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/1bd99d3a02db/fpubh-10-1053298-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/67900fe152b8/fpubh-10-1053298-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/15dc090fcd1c/fpubh-10-1053298-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/a4e45307cd84/fpubh-10-1053298-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/4e65b837db1b/fpubh-10-1053298-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/2249bd2c4690/fpubh-10-1053298-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/db5b3452fb1a/fpubh-10-1053298-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/3336c6a78122/fpubh-10-1053298-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/567758ad5411/fpubh-10-1053298-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/036fdd5955ab/fpubh-10-1053298-g0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/14c7c507c3de/fpubh-10-1053298-g0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/b9846edd2a2b/fpubh-10-1053298-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/1bd99d3a02db/fpubh-10-1053298-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/67900fe152b8/fpubh-10-1053298-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/15dc090fcd1c/fpubh-10-1053298-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/a4e45307cd84/fpubh-10-1053298-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/4e65b837db1b/fpubh-10-1053298-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/2249bd2c4690/fpubh-10-1053298-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/db5b3452fb1a/fpubh-10-1053298-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/3336c6a78122/fpubh-10-1053298-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/567758ad5411/fpubh-10-1053298-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/036fdd5955ab/fpubh-10-1053298-g0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75d7/9731289/14c7c507c3de/fpubh-10-1053298-g0012.jpg

相似文献

1
Using the ISM-ANP-SD combination model to explore the mechanism and intervention strategies of influencing factors of coal mine safety system.运用ISM-ANP-SD 组合模型探究煤矿安全系统影响因素的作用机制及干预策略。
Front Public Health. 2022 Nov 23;10:1053298. doi: 10.3389/fpubh.2022.1053298. eCollection 2022.
2
Analysis of Factors Influencing Miners' Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model.基于一种新型混合 MCDM 模型的智能矿山中矿工不安全行为影响因素分析。
Int J Environ Res Public Health. 2022 Jun 16;19(12):7368. doi: 10.3390/ijerph19127368.
3
Comprehensive Evaluation of Deep Coal Miners' Unsafe Behavior Based on HFACS-CM-SEM-SD.基于 HFACS-CM-SEM-SD 的深部煤矿工人不安全行为综合评价
Int J Environ Res Public Health. 2022 Aug 29;19(17):10762. doi: 10.3390/ijerph191710762.
4
Research on the Construction of a Comprehensive Evaluation Model of Psychological Factors in Coal Mine Workers' Safety: Investigation and Analysis of 1,500 Miners in East China.煤矿工人安全心理因素综合评价模型构建研究：对华东地区1500名矿工的调查与分析
Front Public Health. 2022 Mar 3;10:849733. doi: 10.3389/fpubh.2022.849733. eCollection 2022.
5
Group dynamics analysis and the correction of coal miners' unsafe behaviors.群体动力分析与煤矿工人不安全行为矫正。
Arch Environ Occup Health. 2021;76(4):188-209. doi: 10.1080/19338244.2020.1795610. Epub 2020 Aug 13.
6
Evaluating Targeted Intervention on Coal Miners' Unsafe Behavior.评估针对煤矿工人不安全行为的干预措施。
Int J Environ Res Public Health. 2019 Feb 1;16(3):422. doi: 10.3390/ijerph16030422.
7
Dynamic assessment and system dynamics simulation of safety risk in whole life cycle of coal mine.煤矿全生命周期安全风险的动态评估与系统动力学模拟。
Environ Sci Pollut Res Int. 2023 May;30(23):64154-64167. doi: 10.1007/s11356-023-26958-7. Epub 2023 Apr 15.
8
Risk Assessment of Miners' Unsafe Behaviors: A Case Study of Gas Explosion Accidents in Coal Mine, China.矿工不安全行为风险评估：以中国煤矿瓦斯爆炸事故为例。
Int J Environ Res Public Health. 2019 May 18;16(10):1765. doi: 10.3390/ijerph16101765.
9
Influencing Factors, Formation Mechanism, and Pre-control Methods of Coal Miners' Unsafe Behavior: A Systematic Literature Review.煤矿工人不安全行为的影响因素、形成机制及预控方法：系统文献综述。
Front Public Health. 2022 Mar 7;10:792015. doi: 10.3389/fpubh.2022.792015. eCollection 2022.
10
A simulation experiment study to examine the effects of noise on miners' safety behavior in underground coal mines.一项关于考察噪声对煤矿井下矿工安全行为影响的模拟实验研究。
BMC Public Health. 2021 Feb 9;21(1):324. doi: 10.1186/s12889-021-10354-2.

引用本文的文献

1
Designing green robots with environmental sustainability by applying the concept of multi-criteria decision making.通过应用多标准决策概念设计具有环境可持续性的绿色机器人。
Sci Rep. 2025 Jul 2;15(1):22749. doi: 10.1038/s41598-025-07605-2.
2
Research on the mechanism of human-machine security collaboration of miners considering automation trust.考虑自动化信任的矿工人机安全协作机制研究
Heliyon. 2024 Oct 16;10(23):e39456. doi: 10.1016/j.heliyon.2024.e39456. eCollection 2024 Dec 15.
3
The application obstacles of BIM technology in green building project and its key role path analysis.

本文引用的文献

1
Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model.基于机器学习的煤矿安全评价：BP 神经网络模型。
Comput Intell Neurosci. 2022 Mar 14;2022:5233845. doi: 10.1155/2022/5233845. eCollection 2022.
2
Distributed situation awareness: From awareness in individuals and teams to the awareness of technologies, sociotechnical systems, and societies.分布式情境意识：从个体和团队的意识到技术、社会技术系统和社会的意识。
Appl Ergon. 2022 Jan;98:103599. doi: 10.1016/j.apergo.2021.103599. Epub 2021 Oct 14.
3
Group cohesion in group-based personal practice.
BIM技术在绿色建筑项目中的应用障碍及其关键作用路径分析
Sci Rep. 2024 Dec 5;14(1):30330. doi: 10.1038/s41598-024-81360-8.
基于小组的个人实践中的群体凝聚力。
Behav Cogn Psychother. 2022 Jan;50(1):28-39. doi: 10.1017/S1352465821000369. Epub 2021 Sep 27.
4
Mining Employees Safety and the Application of Information Technology in Coal Mining: Review.煤矿职工安全与信息技术在煤矿中的应用综述
Front Public Health. 2021 Aug 18;9:709987. doi: 10.3389/fpubh.2021.709987. eCollection 2021.
5
Psychosocial safety climate and unsafe behavior among miners in China: the mediating role of work stress and job burnout.矿工的心理社会安全氛围与不安全行为：工作压力和职业倦怠的中介作用。
Psychol Health Med. 2020 Aug;25(7):793-801. doi: 10.1080/13548506.2019.1662068. Epub 2019 Sep 2.
6
Perceived stress in human-machine interaction in modern manufacturing environments-Results of a qualitative interview study.现代制造环境中人机交互的感知压力——定性访谈研究的结果。
Stress Health. 2019 Apr;35(2):187-199. doi: 10.1002/smi.2853. Epub 2019 Jan 30.
7
Introduction matters: Manipulating trust in automation and reliance in automated driving.引言很重要：操纵对自动化的信任和对自动驾驶的依赖。
Appl Ergon. 2018 Jan;66:18-31. doi: 10.1016/j.apergo.2017.07.006. Epub 2017 Aug 12.
8
A Framework to Guide the Assessment of Human-Machine Systems.指导人机系统评估的框架
Hum Factors. 2017 Mar;59(2):172-188. doi: 10.1177/0018720817695077.
9
Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables.运用结构方程模型分析 320 起煤矿事故，将规则和规章的不安全条件作为外生变量。
Accid Anal Prev. 2016 Jul;92:189-201. doi: 10.1016/j.aap.2016.02.021. Epub 2016 Apr 14.
10
System reliability, performance and trust in adaptable automation.系统可靠性、性能以及对自适应自动化的信任。
Appl Ergon. 2016 Jan;52:333-42. doi: 10.1016/j.apergo.2015.07.012. Epub 2015 Aug 28.