Preliminary quantity estimation in construction using machine learning methods
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This paper analyses the problem of estimating the required quantities of major work items in the construction of residential and residential-commercial buildings using machine learning algorithms. The goal is to form a model that will provide a fast and sufficiently accurate estimate of the quantities of major work items, based on a small amount of known information on the technical characteristics and the environment of future residential and residential-commercial buildings. The case study included 71 projects of residential and residential-commercial buildings construction realised on the territory of the Republic of Serbia. Several models have been developed, and the paper presents those models that had the best performances. The models developed in this way can significantly contribute to resource planning and the accuracy of cost estimates in the early project phases.
Keywords:
quantity estimation / cost estimation / machine learning / artificial intelligenceSource:
STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV, 2022Collections
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GraFarTY - CONF AU - Simić, Nevena AU - Petronijević, Predrag AU - Devedžić, Aleksandar AU - Ivanović, Marija PY - 2022 UR - https://grafar.grf.bg.ac.rs/handle/123456789/3223 AB - This paper analyses the problem of estimating the required quantities of major work items in the construction of residential and residential-commercial buildings using machine learning algorithms. The goal is to form a model that will provide a fast and sufficiently accurate estimate of the quantities of major work items, based on a small amount of known information on the technical characteristics and the environment of future residential and residential-commercial buildings. The case study included 71 projects of residential and residential-commercial buildings construction realised on the territory of the Republic of Serbia. Several models have been developed, and the paper presents those models that had the best performances. The models developed in this way can significantly contribute to resource planning and the accuracy of cost estimates in the early project phases. C3 - STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV T1 - Preliminary quantity estimation in construction using machine learning methods DO - 10.7251/STP2215083S ER -
@conference{ author = "Simić, Nevena and Petronijević, Predrag and Devedžić, Aleksandar and Ivanović, Marija", year = "2022", abstract = "This paper analyses the problem of estimating the required quantities of major work items in the construction of residential and residential-commercial buildings using machine learning algorithms. The goal is to form a model that will provide a fast and sufficiently accurate estimate of the quantities of major work items, based on a small amount of known information on the technical characteristics and the environment of future residential and residential-commercial buildings. The case study included 71 projects of residential and residential-commercial buildings construction realised on the territory of the Republic of Serbia. Several models have been developed, and the paper presents those models that had the best performances. The models developed in this way can significantly contribute to resource planning and the accuracy of cost estimates in the early project phases.", journal = "STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV", title = "Preliminary quantity estimation in construction using machine learning methods", doi = "10.7251/STP2215083S" }
Simić, N., Petronijević, P., Devedžić, A.,& Ivanović, M.. (2022). Preliminary quantity estimation in construction using machine learning methods. in STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV. https://doi.org/10.7251/STP2215083S
Simić N, Petronijević P, Devedžić A, Ivanović M. Preliminary quantity estimation in construction using machine learning methods. in STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV. 2022;. doi:10.7251/STP2215083S .
Simić, Nevena, Petronijević, Predrag, Devedžić, Aleksandar, Ivanović, Marija, "Preliminary quantity estimation in construction using machine learning methods" in STEPGRAD2022 - Proceedings of International conference on Contemporary Theory and Practice in Construction XV (2022), https://doi.org/10.7251/STP2215083S . .