基于混合重要性回归集成方法的建设项目成本估算新模型

IF 0.8 Q4 ENGINEERING, INDUSTRIAL
Ali Alkhuadhan, S. Naimi
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引用次数: 0

摘要

成本估算包括收集和评估历史数据,以及使用定量模型、方法、工具和数据库来预测未来项目的成本。在建筑设计过程的早期阶段,成本被认为是决策中最重要的因素之一。在项目的设计阶段,成本估算是非常重要的。设计一个实用的建筑工程造价估算模型和方法,是建设项目成功实施的关键。基于上述原因,本研究开发了一种混合方法来对伊拉克的建设项目进行准确的成本估算。本研究还对伊拉克市场进行了严格的调查,找出了五个主要影响因素和三十六个子因素。通过之前的研究、问卷调查和对20个项目的调查对其进行了评估,以建立建筑项目的矩阵因素数据库。本工作从相关研究和专家观点中收集了施工成本因素。在第二步中,研究人员在重要性回归集合方法中对因素进行排序,然后应用K近邻方法来指定近有效因素对成本的影响。本研究的结果将有助于建筑专业人员有效地评估建筑项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new model for cost estimation construction project using Hybrid importance regression ensemble method
Cost estimating entails gathering and evaluating historical data, as well as using quantitative models, methodologies, tools, and databases to forecast the cost of a program in the future. At the early stages of the building design process, the cost is considered one of the most important elements in making decisions. During the design phase of a project, cost estimating is quite essential. To compelet a construction project successfully, it is critical to design a usable model and method for cost estimation in construction projects. For the above reason, this study has developed a hybrid method to conduct an accurate cost estimation in construction projects in Iraq. This study also conducted a rigorous survey to find five main influential factors with thirty-six sub-factors in the Iraqi market. It was evaluated through previous studies, questionnaires, and surveys of twenty projects to build a matrix factors database for construction projects. This work gathered the construction cost factors from relevant research and expert views. In the second step, the researcher ranked the factors within the Importance Regression Ensemble Method then the K-Nearest Neighbor Method was applied to specify the effect of the near-effective factors on the cost. The outcome of this study will be helpful to construction professionals in estimating a construction project effectively.
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来源期刊
Acta Logistica
Acta Logistica Engineering-Industrial and Manufacturing Engineering
CiteScore
1.80
自引率
28.60%
发文量
36
审稿时长
4 weeks
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