학술논문
基于G-FAHP的深基坑施工风险评价 / Construction Risk Evaluation of Deep Foundation Pit Based on G-FAHP
Document Type
Academic Journal
Author
Source
土木工程与管理学报. 33(5):104-109
Subject
Language
Chinese
ISSN
2095-0985
Abstract
深基坑工程具有施工技术难度大、施工环境复杂、较强的环境效应等特点，且面临着各种不确定性风险因素，是一项综合性很强的系统工程，因此对深基坑施工风险进行科学有效的评估显得尤为重要。本文从系统的角度对影响深基坑施工的风险因素进行收集和划分，建立了深基坑施工风险评价指标体系；并将模糊层次分析法与灰色系统理论结合应用，构建了综合考虑各种风险因素的模糊和灰色不确定性的G-FANP评价模型。最终通过实证分析，得到各指标的风险排序，验证了该方法的可行性。
Deep foundation pit has characteristics of high technical difficulty, complex construction environment and strong environmental effect etc, and it faces various kinds of uncertain risk factors, which is a comprehensive systems engineering, so it is very important to evaluate the risk of deep foundation pit construction scientifically and effectively. The risk factors affecting the construction of deep foundation pit are collected and classified from the view of the system, and the deep foundation pit construction risk evaluation index system is established. Then the fuzzy analytic hierarchy process and grey system theory are combined to construct a G-FANP evaluation model considering the fuzzy and grey uncertainty of various risk factors. Finally, the risk ranking of each index is obtained through empirical analysis, which verifies the feasibility of the method.
Deep foundation pit has characteristics of high technical difficulty, complex construction environment and strong environmental effect etc, and it faces various kinds of uncertain risk factors, which is a comprehensive systems engineering, so it is very important to evaluate the risk of deep foundation pit construction scientifically and effectively. The risk factors affecting the construction of deep foundation pit are collected and classified from the view of the system, and the deep foundation pit construction risk evaluation index system is established. Then the fuzzy analytic hierarchy process and grey system theory are combined to construct a G-FANP evaluation model considering the fuzzy and grey uncertainty of various risk factors. Finally, the risk ranking of each index is obtained through empirical analysis, which verifies the feasibility of the method.