AREA BASE OF COST ESTIMATION FOR BUILDING CONSTRUCTION PROJECTS USING AN ARTIFICIAL NEURAL NETWORK

Yıl 2024, , 113 - 125, 30.06.2024

Nooralhuda Alabdalı

https://doi.org/10.53600/ajesa.1206925

Öz

Managers of projects monitor the project schedule and compare planning values with the actual cost into the project and how much of it is earned value. One of success methods for managing the construction projects is to find the effective cost factors and investigate the correlations between them. In order to determine the discrepancies, the Execution Phase performance measures are compared to the baseline metrics decided upon in the Planning Phase. The significance of these deviations is assessed by factoring them into the control methods at every stage. For that, the present paper developed an ANN technique for project management to monitor the cost of project based on the correlation between the project size and the project cite area within the implementation process. The contribution in this paper is to present a project planning cost mimic the real actual cost. Modifications to the project can be monitored using this method, which takes into account both the nature of the work being done and the time frame during which it is being performed. To gauge the system's efficacy, the ANN system was applied to structural concrete and building walls. The system's final output demonstrated a straightforward and reliable method of tracking and observing progress.

Anahtar Kelimeler

PV, ANN, Project Building Area, Project Site Area

Kaynakça

• Adillah Ismail, Noor Akmal, Erezi Utiome, Robert Owen, and Robin Drogemuller. 2015. “Exploring Accuracy Factors in Cost Estimating Practice towards Implementing Building Information Modelling (BIM).” (January):364–73. doi: 10.32738/ceppm.201509.0036.
• Ahn, Joseph, Hyun-soo Lee, Moonseo Park, and Sae-hyun Ji. 2010. “Cost Estimation for Buildings Using Parameter Impact.” (November 2010).
• Alqahtani, Ayedh, and Andrew Whyte. 2013. “Artificial Neural Networks Incorporating Cost Significant Items towards Enhancing Estimation for (Life-Cycle) Costing of Construction Projects.” Australasian Journal of Construction Economics and Building 13(3):51–64. doi: 10.5130/ajceb.v13i3.3363.
• Amusan, Lekan, Dosunmu Dolapo, and Opeyemi Joshua. 2017. “Cost and Time Performance Information of Building Projects in Developing Economy.” International Journal of Mechanical Engineering and Technology 8(10):918–27.
• Arafa, Mohammed, and Mamoun Alqedra. 2010. “Early Stage Cost Estimation of Buildings Construction Projects Using Artificial Neural Networks.” Journal of Artificial Intelligence 4(1):63–75. doi: 10.3923/jai.2011.63.75.
• Bakhary, Norhisham, Khairulzan Yahya, and Chin Nam Ng. 2012. “Univariate Artificial Neural Network in Forecasting Demand of Low Cost House in Petaling Jaya.” Jurnal Teknologi (June):1–16. doi: 10.11113/jt.v40.406.
• Chimdi, Jifara, Sisay Girma, Alemu Mosisa, and Degefe Mitiku. 2020. “ASSESSMENT OF FACTORS AFFECTING ACCURACY OF COST ESTIMATION IN PUBLIC BUILDING CONSTRUCTION PROJECTS IN WESTERN OROMIA REGION, ETHIOPIA.” 11(2). doi: 10.33736/jcest.2248.2020.
• Dong, Jiacheng, Yuan Chen, and Gang Guan. 2020. “Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks.” Advances in Civil Engineering 2020. doi: 10.1155/2020/6518147.
• Eliufoo, Harriet. 2018. “Risk Factors in Cost Estimation: Building Contractors’ Experience.” American Journal of Civil Engineering and Architecture 6(3):123–28. doi: 10.12691/ajcea-6-3-5.
• Firoozabadi, Kamran Jamali, Saeed Rouhani, and Nazanin Bagheri. 2013. “Review of EPC Projects Cost Estimation and Minimum Error Technique Introduction.” 2(12):1–7.
• Fry, Timothy D., Robert A. Leitch, Patrick R. Philipoom, and Yu Tian. 2016. “Empirical Analysis of Cost Estimation Accuracy in Procurement Auctions.” International Journal of Business and Management 11(3):1. doi: 10.5539/ijbm. v11n3p1.
• Gransberg, Douglas D., H. David Jeong, Ilker Karaca, Brendon Gardner, and H. David. 2017. “Top-Down Construction Cost Estimating Model Using an Artificial Neural Network Recommended Citation.”
• Günaydin, H. Murat, and S. Zeynep Doǧan. 2004. “A Neural Network Approach for Early Cost Estimation of Structural Systems of Buildings.” International Journal of Project Management 22(7):595–602. doi: 10.1016/j.ijproman.2004.04.002.
• Harb, Aws Ahmed. 2016. “Cost Control in Building Construction: Inhibiting Factors and Potential Improvements Cost Overruns in Construction Projects View Project.” (October 2016).
• Ibrahim, Ahmed H., and Lamiaa M. Elshwadfy. 2021. “Assessment of Construction Project Cost Estimating Accuracy in Egypt.” The Open Civil Engineering Journal 15(1):290–98. doi: 10.2174/1874149502115010290.
• Juszczyk, Michał, Agnieszka Leśniak, and Krzysztof Zima. 2018. “ANN Based Approach for Estimation of Construction Costs of Sports Fields.” Complexity 2018. doi: 10.1155/2018/7952434.
• Malkanthi, S. N., A. G. D. Premalal, and R. K. P. C. B. Mudalige. 2017. “Impact of Cost Control Techniques on Cost Overruns in Construction Projects.” Engineer: Journal of the Institution of Engineers, Sri Lanka 50(4):53. doi: 10.4038/engineer. v50i4.7275.
• Matel, Erik, Faridaddin Vahdatikhaki, Siavash Hosseinyalamdary, Thijs Evers, and Hans Voordijk. 2019. “An Artificial Neural Network Approach for Cost Estimation of Engineering Services.” International Journal of Construction Management. doi: 10.1080/15623599.2019.1692400.
• Oke, Ayodeji Emmanuel, and Clinton Aigbavboa. 2019. “Influences of Project Cost Estimation in South African Construction Industry Influences of Project Cost Estimation in South African Construction.” (August).
• Palikila R. 2015. “Cost Planning and Cost Management in Construction Projects.” (December 2009).
• Roxas, Cheryl Lyne C., and Jason Maximino C. Ongpeng. 2014. “An Artificial Neural Network Approach to Structural Cost Estimation of Building Projects in the Philippines.” DLSU Research Congress 1–8.
• Salunkhe, Ashwini Arun. 2020. “Comparative Analysis of Construction Cost Estimation Using Artificial Neural Networks.” Journal of Xidian University 14(7). doi: 10.37896/jxu14.7/146.
• Shabani, Mohammed. 2015. “Suitable Method for Capital Cost Estimation in Chemical Processes Industries.” Cost Engineering 48/No 5 Ma(September):1–5. doi: 10.13140/RG.2.1.1545.7762.
• Weckman, Gary R., Helmut W. Paschold, John D. Dowler, Harry S. Whiting, and William A. Young. 2010. “Using Neural Networks with Limited Data to Estimate Manufacturing Cost.” Journal of Industrial and Systems Engineering 3(4):257–74.