Conceptual cost estimation of building projects with regression analysis and neural networks

Date

2004-08-01

Author

Sönmez, Rifat

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Conceptual cost estimates play a crucial role in initial project decisions, although scope is not finalized and very limited design information is available during early project stages. In this paper, the advantages and disadvantages of the current conceptual cost estimation methods are discussed and the use of regression, neural network, and range estimation techniques for conceptual cost estimation of building projects are presented. Historical cost data of continuing care retirement community projects were compiled to develop regression and neural network models. Three linear regression models were considered to identify the significant variables affecting project cost. Two neural network models were developed to examine the possible need for nonlinear or interaction terms in the regression model. Prediction intervals were constructed for the regression model to quantify the level of uncertainty for the estimates. Advantages of simultaneous use of regression analysis, neural networks, and range estimation for conceptual cost estimating are discussed.

Subject Keywords

Degradation pattern, Hydrocarbon bioremediation, Kerosene, N-alkanes

URI

https://hdl.handle.net/11511/32794

Journal

CANADIAN JOURNAL OF CIVIL ENGINEERING

DOI

https://doi.org/10.1139/l04-029

Collections

Department of Civil Engineering, Article

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Citation Formats

R. Sönmez, “Conceptual cost estimation of building projects with regression analysis and neural networks,” CANADIAN JOURNAL OF CIVIL ENGINEERING, pp. 677–683, 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32794.