Bridge Construction Cost Prediction using Multiple Linear Regression
Krishna Garkal1, N.B. Chaphalkar2, Sayali Sandbhor3

1Krishna Garkal, Former Post Graduate Student, Civil Engineering Department, College of Engineering, Pune, India.
2Dr. N.B. Chaphalkar, Former Associate Professor, Civil Engineering Department, College of Engineering, Pune, India.
3Dr. Sayali Sandbhor, Assistant Professor, Civil Engineering Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India.

Manuscript received on 04 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 July 2019 | PP: 3115-3121 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8916078919/19©BEIESP | DOI: 10.35940/ijitee.I8916.078919

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Abstract: Cost of construction of bridges is predicted using multiple linear regression model, based on data of bridges from Maharashtra state in India. Cost per unit area is taken as an appropriate dependent variable. Using both conventional and double log regression techniques, models for cost/m2 and log of cost/m2 are developed. Total 6 independent variables, which include both qualitative and quantitative variables, are used to develop the model. Height of bridge, average span length and depth of foundation are used as quantitative variables. Zone of construction, deck type and foundation type are used as qualitative variables in developing model. Strength of these independent variables with dependent variable is found out using pearson’s correlation method. Model is then verified using Leave One Out Cross Validation (LOOCV) technique. The most suited regression model obtained from the data experiment is double log regression with R2 of 0.850 and a Mean Absolute Percentage Error (MAPE) of 17.74%, as compared to 25% MAPE observed in past for studies related to traditional cost prediction.
Keywords: Bridge, Multiple Linear Regression, Prediction, Construction Cost, Cost Model

Scope of the Article: Construction Engineering