基于改进可拓云模型的装配式建筑施工安全风险评价方法
Safety risk evaluation method for assembly building construction based on improved tractable cloud
于治成 1陆红梅 1吴松 2从明智1
作者信息
- 1. 石河子大学水利建筑工程学院,新疆 石河子 832000
- 2. 新疆天富远大建筑产业化有限公司,新疆 石河子 832000
- 折叠
摘要
为保障装配式建筑施工安全,考虑到施工安全指标因素的模糊性与随机性,运用组合赋权-改进可拓云模型对施工安全风险进行评价.首先,从"三度空间"视角下,在物理、社会、信息三个层面构建了评价指标体系;其次,运用改进的层次分析法(AHP)和熵权法(EW)确定主客观权重,基于距离函数确定综合权重,根据云理论和可拓学理论提出一种云熵确定方法,对传统可拓云模型进行改进后构建评价模型;最后,将该模型运用到工程实例中,与其他模型进行对比.结果表明:该施工项目评价等级为很安全,且具有很高的可信度;验证了该模型的可靠性和可行性,为装配式建筑施工安全风险评价提供了一种更加科学、准确的评价方法.
Abstract
In order to ensure the construction safety of assembled buildings,considering the ambiguity and randomness of the construction safety index factors,the combined empowerment-improved topological cloud model is used to evaluate the construction safety risk.Firstly,the evaluation index system is constructed from the perspective of"three-degree space"in the physical,social and information levels;secondly,the subjective and objective weights are determined by the improved hierarchical analysis method(AHP)and entropy weighting method(EW),and the comprehensive weights are determined based on the distance function,and a method of determining the entropy of the cloud is proposed according to the cloud theory and the theory of topology,and propose a cloud entropy determination method and improve the traditional topological cloud model,and construct the evaluation model;finally,the model is applied to the engineering example and compared with other models.The results show that the evaluation grade of the construction project is very safe and has high credibility;the reliability and feasibility of the model are verified,providing a more scientific and accurate evaluation method for the safety risk evaluation of assembly building construction.
关键词
三度空间/装配式建筑/可拓云模型/改进层次分析法(AHP)/熵权法(EW)/施工安全风险评价Key words
three degrees of space/assembled building/topological cloud model/improved hierarchical analysis/entropy weight method/construction safety risk evaluation引用本文复制引用
基金项目
新疆生产建设兵团重点领域科技攻关计划项目(2021AB027)
出版年
2024
NETL
NSTL
万方数据