Research on Influencing Factors of Total Construction Contract Cost Based on Multiple-Factor Regression Analysis and Prediction Model
Publication: ICCREM 2023
ABSTRACT
In the construction of engineering projects, it is of great significance to know the factors affecting the total construction contract fee and realize the prediction of the total construction contract fee for the operation and management of the owner and the construction side. Through the analysis of literature and relevant books, 18 factors affecting the total construction contract cost are sorted out. Based on real data collection, first by factor analysis to extract the common factors that affects the cost of construction general contracting, according to the principal component factor loading, determine the key factors influencing the construction of the total contract fee, and then adopt the method of multiple regression analysis of common factor, and establish the mathematical model for quantitative prediction, finally through the test validation. It is concluded that the prediction model is accurate and has great reference value for the prediction of total construction contract cost.
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REFERENCES
Arage, S.S., and Dharwadkar, N.V. (2017). “Cost estimation of civil construction projects using machine learning paradigm.” In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, 594-599.
Chan, S.L., and Park, M. (2005). “Project cost estimation using principal component regression.” Construction Management and Economics, 23(3), 295-304.
Chen, X.L., and Wang, L.G. (2009). “Project cost estimation based on analysis model of architectural design parameters”. Acta Tongji University: Natural Sciences, 37(8), 1115-1121.
Kadri, T., and Sugara, R.D.H. (2017). “Estimated budget construction housing using linear regression model easy and fast solutions accurate.” In 2017 International Conference on Computing, Engineering, and Design (ICCED), Kuala Lumpur, Malaysia, 1-6.
Ke, H. (2017). Construction Project Valuation. China Planning Press, Beijing. (in Chinese).
Li, W. (2015). “The multi-element structure whole linear regression model of the construction project cost forecast”. Building Technology, 46(9), 846-849. (in Chinese).
Liu, J., and Ye, Q. (2013). “Project cost prediction model in Xiamen based on BP and RBF Neural Network”. Acta Huaqiao University: Natural Sciences, 34(5), 576-580. (in Chinese).
Liu, Y., and Lai, X. (2010). “Study on the estimation method of civil engineering investment based on multiple linear regression and engineering cost inversion”. Acta Qinghai Normal University: Natural Sciences, 26(1), 92-97. (in Chinese).
Liang, X., and Liu, Y. (2017). “Construction cost prediction model based on fuzzy neural network.” Technical Economics, 36(3), 109-113. (in Chinese).
Li, S.Q. (2017). Modeling Study on Rapid Cost Estimation of Construction Engineering. South China University of Technology, Guangzhou, China, 84. (in Chinese).
Liu, Y.N. (2016). Research on Valuation of Construction Projects Based on Artificial Intelligence. Shenyang Jianzhu University, Shenyang, China, 81. (in Chinese).
Liu, S.A. (2022). Research on Construction Cost Prediction Based on XGBoost Algorithm. Beijing University of Civil Engineering and Architecture, Beijing, China, 72. (in Chinese).
Qin, Z.F., Lei, X.L., and Zhai, D. et al. (2016). “Research on residential engineering cost prediction based on SVM and LS-SVM.” Journal of Zhejiang University: Science Edition, 43(3), 357-363. (in Chinese).
Wang, Y. (2020). Estimated Forecasting of Residential Engineering Based on BP Neural Network. Lanzhou Jiaotong University, Lanzhou, China, 97. (in Chinese).
Wang, S. (2018). Construction Cost Prediction Based on Particle Swarm Optimization Least Squares Support Vector Machine. Qingdao University of Technology, Qingdao, China, 95. (in Chinese).
Xu, L., and Li, Z.R. (2017). “Study on engineering cost prediction model of UHV transmission line based on factor analysis and BP neural network.” Industrial Technical Economy, 36(7), 18-26. (in Chinese).
Xie, R.F. (2016). Construction Cost Prediction Based on Adaptive Fuzzy Neural Network. Wuhan University of Science and Technology, 70. (in Chinese).
Zhu, S.S. (2015). “Talking about the factors that affect the project cost of the general contract of enterprise construction.” Economic Market of Science and Technology, (06), 178-178. (in Chinese).
Zheng, B.J. (2012). “This paper discusses some factors affecting the engineering cost of the general contract project.” Value Engineering, 31(30), 74-76. (in Chinese).
Zhu, Y.X. (2015). “Study on engineering cost estimation method based on ISM and multiple regression analysis model.” Construction, 37(2), 245-248. (in Chinese).
Zou, Y.P., and Sun, W.G. (2021). “The application of multiple linear regression in the quota design of landscape architecture project.” Chinese Gardens, 37(06), 87-92. (in Chinese).
Zou, M.S., Gu, X., and Shi, H.C. (2022). “Construction of engineering cost forecasting model based on stepwise regression.” Automation and Applications, 41(03), 162-166. (in Chinese).
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Published online: Nov 30, 2023
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