Early Estimation of Sewerage Line Costs with Regression Analysis

Yıl 2022, Cilt: 35 Sayı: 3, 822 - 832, 01.09.2022

Murat Sueri Mürsel Erdal

https://doi.org/10.35378/gujs.949726

Cited By: 3

Öz

In Turkey, an average of 450 sewer line tenders are made annually and the total line length of these works is approximately 11000000 m. It is very important for both the investor and the contractor to know the costs of the sewer networks with such a large business volume. In this study, models are developed for early estimation of sewage line costs by the regression analysis method. Data belonging to 182 sewer line projects were used in the development of the models. Data on pipe diameter, line length, excavation depth, manhole amount, excavation amount, filling amount, filling type, shoring type, excavation class and real cost parameters were determined through the projects. Correlations between the determined parameters were specified and the parameters suitable for regression analysis were selected. As a result; among the developed estimation models, the equation using all selected parameters with a correlation coefficient of R² = 0.911 gave the most successful result.

Anahtar Kelimeler

Sewerage line, Cost estimation, Regression analysis (RA)

Kaynakça

• [1] Topçu, G., “Cost-related operations in the building production process: estimation, planning, control”, MS Thesis, İstanbul Technical University, İstanbul, 25-32, (1989).
• [2] Uğur, L.O., Kanıt, R., Erdal, H., Namlı, E., Erdal, H.İ., Baykan, U.N., Erdal, M., “Enhanced predictive models for construction costs: A case study of Turkish mass housing sector”, Computational Economics, 53(4): 3336-3344, (2019).
• [3] Polat, A.P., Çıracı, M., “A database model for pre-design-phase building cost estimate in Turkey”, İTÜ Journal/a, 4(2): 59-69, (2005).
• [4] Özmaden, M.Ş., Erdal, M., “Performance analysis of methods used in the cost estimation of residential buildings”, Konya Journal of Engineering Sciences, 8(4): 970-985, (2020).
• [5] Kanıt, R., Baykan, U.N., Erdal, M., “Investigation of the effects of constrained source conditions on the structure cost”, Journal of Polytechnic, 8(2): 209-221, (2005).
• [6] Özyürek, İ., Erdal, M., “Assessment of qualification criteria described in Public Procurement Law Code 4734 in construction works by analytic hierarchy process (AHP)”, Gazi University Journal of Science, 31(2): 437-454, (2018).
• [7] Yıldız, S., Kıvrak, S., Gültekin, A.B., Arslan, G., “Built environment design - social sustainability relation in urban renewal”, Sustainable Cities and Society, 60:102173, (2020).
• [8] Elazouni, A.M., Nosair, I.A., Mohieldin, Y.A., Mohamed, A.G., “Estimating resource requirements at conceptual design stage using neural networks”, Journal of Computing in Civil Engineering, 11: 217-223, (1997).
• [9] Kim, G.H., An, S.H., Kang, K.I., “Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning”, Building and Environment, 39: 1235-1242, (2004).
• [10] Sodikov, J., “Cost estimation of highway projects in developing countries: Artificial neural network approach”, Journal of the Eastern Asia Society for Transportation Studies, 6: 1036-1047, (2005).
• [11] Baykan, U.N., “Estimating resource requirements of construction projects with artificial neural networks approach”, PhD Thesis, Gazi University, Ankara, 88-90, (2007).
• [12] Öztürk, E., “Cost Estimation Of Trackworks Of Light Rail And Metro Projects”, MS Thesis, METU, Ankara, 81-83, (2009).
• [13] Bahadır, Y., “Using artifical neural networks (ANN) for estimation of the bid price of glass fibre reinforced cladding elements”, MS Thesis, İstanbul Technical University, İstanbul, 55-58, (2013).
• [14] Kasaplı, K., “Artificial neural networks usage for cost estimating on the water supply networks”, MS Thesis, İstanbul Technical University, İstanbul, 75-80, (2014).
• [15] Rui, Z.H., Metz, P.A., Reynolds, D.B., Chen, G., Zhou, X.Y., “Historical pipeline construction cost analysis”, International Journal of Oil Gas and Coal Technology, 4(3): 244-263, (2011).
• [16] Rui, Z.H., Metz, P.A., D.B., Chen, G., “An analysis of inaccuracy in pipeline construction cost estimation”, International Journal of Oil Gas and Coal Technology, 5(1): 29-46, (2012).
• [17] Clements, KW., Si, J.W., “The investment project pipeline: cost escalation, lead time, success, failure and speed”, Australian Journal of Management, 36(3): 317-348, (2011).
• [18] Kaiser, M. J., Liu, M., “Cost factors and statistical evaluation of gas transmission pipeline construction and compressor-station cost in the USA, 2014-2019”, International Journal of Oil Gas and Coal Technology, 26(4): 422-452, (2021).
• [19] Kaiser, M. J., “A review of onshore and offshore pipeline construction and decommissioning cost in the USA - part 1: specifications, cost estimation and onshore construction”, International Journal of Oil Gas and Coal Technology, 27(3): 247-285, (2021).
• [20] Kaiser, M. J., “A review of onshore and offshore pipeline construction and decommissioning cost in the USA - part 2. Offshore and deepwater decommissioning cost algorithms”, International Journal of Oil Gas and Coal Technology, 27(4): 363-398, (2021).
• [21] Neter, J., Kunter, M., Nachtsheim, W., Wasserman, C., “Applied Linear Regression Models”, The Mc Graw-Hill Companies Inc., Chicago, (1996).
• [22] Gündüz, M., Uğur, L.O., Öztürk, E., “Parametric cost estimation system for light rail transit and metro trackworks”, Expert Systems with Applications, 38(3): 2873-2877, (2011).
• [23] Yılmaz, M., Kanıt, R., Erdal, M., Yıldız, S., Bakış, A., “Determination of the factors effecting the tender price by way of artificial neural networks and linear regression analyses in order to utilize maintenance and repair funds more effectively”, Journal of Polytechnic, 19(4): 461-470, (2016).
• [24] Bostancıoğlu, E., “Residential building envelope alternatives with equivalent cost”, Gazi University Journal of Science, 24(2): 355-363, (2011).
• [25] Sueri, M., “Estimating sewer line costs with artificial neural networks”, MS Thesis, Gazi University, Ankara, 21-35, (2016).