The reinforced concrete retaining walls (RCRWs) are constructed many civil engineering projects such as highway, railway, building etc. Many different design constraints must be considered in the design of RCRWs. In the traditional approach, the design variables are controlled many times by trial-error process to provide the optimum design, thus the optimization techniques must be used to save on time for project managers. The other important subject in civil engineering projects is to estimate correctly the cost of the project before the construction for the tender process. In the first stage of the study, 125 optimization problems for the RCRW, which are sitting on strong soil layer, are analyzed for different combinations of wall heights, surcharge loads and internal friction angles of the backfill soil by use of the modified artificial bee colony (ABC) algorithm, and minimum costs are determined. Then, the multiple regression and artificial neural network models are presented for minimum cost estimation of the wall. The cost estimations obtained from the proposed models are in great agreement with the calculated values by the modified ABC algorithm. The error values between predicted and calculated minimum costs are almost zero. The results show that the proposed models can be successfully used for minimum cost estimation of the RCRWs sitting on strong soil layer.
: 14 Kasım 2019
|APA||DAĞDEVİREN, U , KAYMAK, B . (2020). Cost Estimation Models for the Reinforced Concrete Retaining Walls. Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi , 7 (100. Yıl Özel Sayı) , 9-26 . DOI: 10.35193/bseufbd.646668|