The Control of Civil Engineering Projects Based on Deep Learning and Building Information Modeling

The Control of Civil Engineering Projects Based on Deep Learning and Building Information Modeling

Fang Wang, Liangqiong Chen
Copyright: © 2023 |Pages: 14
DOI: 10.4018/IRMJ.329250
Article PDF Download
Open access articles are freely available for download

Abstract

The aim of this study is to enhance the quality of civil engineering project management and optimize project control in order to ensure adequate construction resources and facilitate seamless project progression. By integrating building information modeling (BIM) technology with deep learning techniques, optimal control was examined at various stages of civil engineering project management. A simulation test was performed on a selected gymnasium engineering project, focusing on cost and resource control aspects. The findings revealed that, as the project advanced, the planned cost exceeded the actual cost by nearly 100,000 yuan in the final stage. The combination of BIM technology and deep learning model prediction substantially reduced the cost and material budgets of the engineering project. Data analysis showed that the average positioning error of the convolutional neural network algorithm for the project model was below 2%.
Article Preview
Top

Literature Review

Tsai et al. (2014) investigated a new methodology for critical success factors (CSFs) that can be used to further develop research for more effective evaluation of buildings. Jung et al. constructed a BIM application framework for evaluating the value of BIM applications, assessed the level of practical application of BIM technology in three levels and six dimensions, and illustrated the driving reasons for increasing the value of using BIM technology.

Complete Article List

Search this Journal:
Reset
Volume 37: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 36: 1 Issue (2023)
Volume 35: 4 Issues (2022): 3 Released, 1 Forthcoming
Volume 34: 4 Issues (2021)
Volume 33: 4 Issues (2020)
Volume 32: 4 Issues (2019)
Volume 31: 4 Issues (2018)
Volume 30: 4 Issues (2017)
Volume 29: 4 Issues (2016)
Volume 28: 4 Issues (2015)
Volume 27: 4 Issues (2014)
Volume 26: 4 Issues (2013)
Volume 25: 4 Issues (2012)
Volume 24: 4 Issues (2011)
Volume 23: 4 Issues (2010)
Volume 22: 4 Issues (2009)
Volume 21: 4 Issues (2008)
Volume 20: 4 Issues (2007)
Volume 19: 4 Issues (2006)
Volume 18: 4 Issues (2005)
Volume 17: 4 Issues (2004)
Volume 16: 4 Issues (2003)
Volume 15: 4 Issues (2002)
Volume 14: 4 Issues (2001)
Volume 13: 4 Issues (2000)
Volume 12: 4 Issues (1999)
Volume 11: 4 Issues (1998)
Volume 10: 4 Issues (1997)
Volume 9: 4 Issues (1996)
Volume 8: 4 Issues (1995)
Volume 7: 4 Issues (1994)
Volume 6: 4 Issues (1993)
Volume 5: 4 Issues (1992)
Volume 4: 4 Issues (1991)
Volume 3: 4 Issues (1990)
Volume 2: 4 Issues (1989)
Volume 1: 1 Issue (1988)
View Complete Journal Contents Listing