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Predicting cost of prefabricated housing using neural networks (CROSBI ID 563857)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Vukomanović, Mladen ; Kararic, Mirsad ; Radujković, Mladen Predicting cost of prefabricated housing using neural networks // Proceedings of the PM-05> Fifth Scientific Conference on Project Management / John-Paris Pantouvakis (ur.). Atena: Center for Construction Innovation, National Technical University of Athens, 2010. str. 40-x

Podaci o odgovornosti

Vukomanović, Mladen ; Kararic, Mirsad ; Radujković, Mladen

engleski

Predicting cost of prefabricated housing using neural networks

Political and economic pressures have become an aggravating circumstance for construction companies in achieving basic project management criteria, i.e. cost, time and scope. The construction's low performance only stresses out the need for improving current practices - especially in regard to cost. Therefore, we sought to find a critical set of variables for predicting total cost of prefabricated housing. We applied neural networks on data from more than 30 projects and thus have identify 17 critical variables for the cost prediction. The model was verified on 28 buildings with following performances: 85.7% of predicted values had the deviation lower 5%, while 10.7% had the deviation lower than 10%, in relation to the actual cost. After validating the model on data from 3 buildings, that had been new to the network, the performances were as follows: 83.8% of predicted values had the deviation lower 5%, while 12.9% had the deviation lower than 10%. Therefore this model showed to be very robust. Furthermore, this study has also demonstrated a more efficient and effective way of predicting total cost of building. Thus construction companies can influence project performance during project early phases, and acquire more competitive position on the market. Conclusion brings guidelines for use of the model and gives recommendation for its further development.

prefabricated housing; prediction; cost; neural networks; model; construction+

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Podaci o prilogu

40-x.

2010.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the PM-05> Fifth Scientific Conference on Project Management

John-Paris Pantouvakis

Atena: Center for Construction Innovation, National Technical University of Athens

978-960-254-690-1

Podaci o skupu

PM-05> Fifth Scientific Conference on Project Management

predavanje

29.05.2010-31.05.2010

Heraklion, Grčka

Povezanost rada

Građevinarstvo