Original scientific paper

https://doi.org/10.17559/TV-20150116001543

Construction costs forecasting: comparison of the accuracy of linear regression and support vector machine models

Silvana Petruseva orcid.org/0000-0002-3752-513X ; Faculty of Civil Engineering, "Ss. Cyril and Methodius" University, Blv. Partizanski Odredi, 24, 1000 Skopje, Republic of Macedonia
Valentina Zileska-Pancovska orcid.org/0000-0001-7620-4040 ; Faculty of Civil Engineering, "Ss. Cyril and Methodius" University, Blv. Partizanski Odredi, 24, 1000 Skopje, Republic of Macedonia
Vahida Žujo orcid.org/0000-0003-3380-5828 ; Faculty of Civil Engineering, University Dzemal Bijedic, Univerzitetski Kampus, 88104 Mostar, Bosnia and Herzegovina
Aida Brkan-Vejzović ; Faculty of Civil Engineering, University Dzemal Bijedic, Univerzitetski Kampus, 88104 Mostar, Bosnia and Herzegovina

Abstract

Each contract for a construction project has the costs as an essential element, so the accuracy of forecasting the construction costs can have an impact on the project realization, and also, on the project participants’ business. Data for structures (75) were used for modelling with two predictive models: linear regression model (LR) and support vector machine (SVM) model, using Bromilow’s model for cost and time relation and predictive modelling software DTREG. The mean absolute percentage error (MAPE) for the SVM model is 0.3% and for the linear regression model is 4.79%. Comparison of the models’ results pointed out that the forecasting with SVM was significantly more accurate.

Keywords

construction costs; forecasting; linear regression; support vector machine

Hrčak ID:

188240

URI

https://hrcak.srce.hr/188240

Publication date:

25.10.2017.

Article data in other languages: croatian

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