Identifying the risk factors affecting the overall cost risk in residential projects at the early stage

被引:24
作者
Badawy, Mohamed [1 ]
Alqahtani, Fahad [2 ]
Hafez, Hisham [3 ]
机构
[1] Ain Shams Univ, Struct Engn Dept, Cairo 11517, Egypt
[2] King Saud Univ, Coll Engn, Dept Civil Engn, POB 800, Riyadh 11421, Saudi Arabia
[3] Univ Northumbria, Dept Mech & Construct Engn, Newcastle Upon Tyne, Tyne & Wear, England
关键词
Overall risk; Artificial Neural Network (ANN); Residential projects; Multilayer perceptron; Data mining; INFRASTRUCTURE PROJECTS; CONSTRUCTION PROJECTS; NEURAL-NETWORKS; MANAGEMENT; IDENTIFICATION; INDUSTRY; RANKING;
D O I
10.1016/j.asej.2021.09.013
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Many previous studies have developed models for estimating the total cost, whether in the planning stage or the early stage of the project. However, models for estimating the overall risk were proposed in the planning stage only. This paper identifies the factors affecting the overall risk in residential projects at the early stage. The 43 risk factors at the planning stage were identified using a Delphi technique. Experts summarize the 43 risk factors into four factors that can be used to predict the overall risk in the early stage of the project. A multilayer perceptron model with one hidden layer was proposed. The mean absolute error rate for the proposed model was 10%. Risk factors can be used to develop a model to predict the impact of overall risk on project cost at the early stage. The developed model helps stakeholders decide whether the project should continue or be terminated. (C) 2021 THE AUTHOR. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University.
引用
收藏
页数:11
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