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分析印尼建筑业安全设计实施因素:一个两阶段的SEM-人工神经网络方法

Rossy A Machfudiyanto¹, Sunkuk Kim², Yusuf Latief¹

¹Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Indonesia, Kampus Baru UI Depok, West Java, 16424, Indonesia.

|November 9, 2023

概括

在印度尼西亚建筑中实施安全设计 (DfS) 对于防止事故至关重要. 合同文件和设计因素对DfS有重大影响,需要行业和政府优先考虑提高工作安全.

科学领域:

建设管理建设管理.
职业安全与健康问题职业安全与健康问题
工程管理工程管理工程管理

背景情况:

印度尼西亚的基础设施发展正在快速增长,但建筑项目的工作安全仍然是一个重大问题.
建筑业的工伤事故是一个重大挑战,需要采取有效的预防策略.
为安全设计 (DfS) 被认为是减轻这些风险的关键策略.

研究的目的:

分析影响印尼建筑项目实施工作安全设计的多种因素.
确定对采用安全设计 (DfS) 原则产生积极影响的关键变量.
通过改进的设计实践,为提高工作安全提供可行的建议.

主要方法:

采用了两个统计方法:结构方程建模 (SEM) 和人工神经网络 (ANN).
SEM用于分析变量及其指标之间的关系模式.
ANN被用来绘制模式并预测影响DfS实施的变量.

主要成果:

几个因素积极影响安全设计 (DfS) 的实施,包括设计师,所有者,政策,工具/设备,知识和合同文件.
设计因素和合同文件被发现是影响DfS实施的最重要的变量.
该研究发现了这些因素与安全在设计中的成功采用之间的正相关性.

结论:

合同文件和设计因素对于加速印尼安全设计 (DfS) 实施至关重要.
行业和政府机构应该在他们的安全计划中优先考虑这些关键变量.
建议对所有已识别的因素进行整体整合,以全面提高工作安全.

关键词:

人工神经网络的人工神经网络建筑工程建筑工程建筑工程设计为安全的设计.设计师设计师设计师结构方程建模结构方程建模

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