一种基于综合权重方法,云模型和COPRAS的混合MCDM方法,用于评估道路建设工人的安全气候
Jing Cai1, Yihui Hu1, Yiming Peng1
1Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China.
Frontiers in public health
|October 11, 2024
概括
本研究引入了一种新的混合模型 (CM-COPRAS) 来评估建筑工人安全气候,预测性能和指导改进. 该模型具有很高的准确性,并验证了有关教育水平和安全的现有研究.
科学领域:
- 建筑安全管理 建筑安全管理
- 职业健康和安全问题 职业健康和安全问题
- 风险评估和风险管理
背景情况:
- 评估安全环境对于预防建筑工地事故至关重要.
- 现有的方法在评估不同工人群体时可能缺乏准确性.
- 有针对性的安全干预需要对特定群体的安全感知有准确的了解.
研究的目的:
- 提出一种新的混合多标准决策 (MCDM) 方法,用于评估不同建筑工人群体的安全气候水平.
- 根据评估的安全气候来预测安全性能.
- 促进实施有针对性的安全改进措施.
主要方法:
- 开发了一种混合MCDM方法,整合了组合权重,云模型 (CM) 和COPRAS.
- 利用BP神经网络和随机森林来学习安全气候标准的权重.
- 采用云模型为各种工人群组构建决策矩阵.
- 应用COPRAS方法对安全气候水平进行比较分析.
主要成果:
- 拟议的CM-COPRAS模型在评估工作年龄,事故经验和工作类型等不同组的安全气候方面表现出高度准确性.
- 教育群体的评估结果显示了轻微的差异,但与现有研究一致,表明教育水平和安全气候之间存在正相关性.
- 该模型与先前研究的一致性验证了其合理性和有效性.
结论:
- 混合CM-COPRAS方法为评估建筑工人安全气候提供了强大的和有效的方法.
- 这些发现支持基于特定组的评估制定有针对性的安全战略.
- 这种方法提高了安全性能的预测,并有助于实施有效的安全改进.
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