Construction cost estimation of reinforced and prestressed concrete bridges using machine learning

Građevinar

article

Miljan Kovačević¹  Nenad Ivanišević²  Predrag Petronijević²  Vladimir Despotović³ 

[1] University of Prishtina Faculty of Technical Sciences;University of Belgrade, Serbia Faculty of Civil Engineering;University of Luxembourg Department of Computing

关键词: reinforced concrete bridges;    machine learning;    prestressed concrete bridges;    construction cost;   

DOI  :  10.14256/JCE.2738.2019

学科分类：社会科学、人文和艺术（综合）

来源: Hrvatsko Drustvo Gradevinskih Inzenjera

【 摘 要 】

Seven state-of-the-art machine learning techniques for estimation of construction costs of reinforced-concrete and prestressed concrete bridges are investigated in this paper, including artificial neural networks (ANN) and ensembles of ANNs, regression tree ensembles (random forests, boosted and bagged regression trees), support vector regression (SVR) method, and Gaussian process regression (GPR). A database of construction costs and design characteristics for 181 reinforced-concrete and prestressed-concrete bridges is created for model training and evaluation.

【 授权许可】

CC BY